Network node memory utilization analysis

ABSTRACT

Systems, methods, and computer-readable media analyzing memory usage in a network node. A network assurance appliance may be configured to query a node in the network fabric for a number of hardware level entries, stored in memory for the node, that are associated with a concrete level network rule. The network assurance appliance may identify a logical level network intent associated with the concrete level network rule, identify a logical level component of the logical level network intent, and attribute the number of hardware level entries to the logical level component.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. provisional patent application62/521,638, filed on Jun. 19, 2017, “NETWORK NODE MEMORY UTILIZATIONANALYSIS,” the contents of which are herein incorporated by reference inits entirety.

TECHNICAL FIELD

The present technology pertains to network configuration andtroubleshooting, and more specifically to analyzing network node memoryutilization.

BACKGROUND

Network configurations for large data center networks are oftenspecified at a centralized controller. The controller can programswitches, routers, servers, and elements in the network according to thespecified network configurations. Network configurations are inherentlyvery complex, and involve low level as well as high level configurationsof several layers of the network such as access policies, forwardingpolicies, routing policies, security policies, QoS policies, etc. Givensuch complexity, the network configuration process is error prone. Theconfigurations are defined on a controller and can reflect an intentspecification for the network. In many cases, the configurations cancontain errors and inconsistencies that are often extremely difficult toidentify and may create significant problems in the network.Furthermore, for various reasons, the configurations defined on thecontroller may be or become inconsistent with the implementation of theintent specification on network nodes.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIGS. 1A and 1B illustrate example network environments, in accordancewith various aspects of the subject technology;

FIG. 2A illustrates an example object model for a network, in accordancewith various aspects of the subject technology;

FIG. 2B illustrates an example object model for a tenant object in theexample object model from FIG. 2A, in accordance with various aspects ofthe subject technology;

FIG. 2C illustrates an example association of various objects in theexample object model from FIG. 2A, in accordance with various aspects ofthe subject technology;

FIG. 2D illustrates a schematic diagram of example models forimplementing the example object model from FIG. 2A, in accordance withvarious aspects of the subject technology;

FIG. 3A illustrates an example network assurance appliance, inaccordance with various aspects of the subject technology;

FIG. 3B illustrates an example system for network assurance, inaccordance with various aspects of the subject technology;

FIG. 3C illustrates a schematic diagram of an example system for staticpolicy analysis in a network, in accordance with various aspects of thesubject technology;

FIG. 4A illustrates an example method for network assurance, inaccordance with various aspects of the subject technology;

FIG. 4B illustrates an example method for generating a device specificlogical model, in accordance with various aspects of the subjecttechnology;

FIG. 5A illustrates an example method embodiment for determining anumber of hardware level entries for a logical level component, inaccordance with various aspects of the subject technology;

FIG. 5B illustrates an example data structure to store an association ofa number of hardware level entries with logical level components, inaccordance with various aspects of the subject technology;

FIGS. 6A-6E illustrate example user interfaces, in accordance withvarious aspects of the subject technology;

FIG. 7 illustrates an example method embodiment for determining whetherconcrete level rules implemented on a node are appropriately configured,in accordance with various aspects of the subject technology;

FIG. 8 illustrates an example method embodiment for determining whetherhardware level entries implemented on a node are appropriatelyconfigured, in accordance with various aspects of the subjecttechnology;

FIG. 9 illustrates an example method embodiment for generating a reporton hit count for various logical level components, in accordance withvarious aspects of the subject technology;

FIG. 10 illustrates an example network device in accordance with variousembodiments; and

FIG. 11 illustrates an example computing device in accordance withvarious embodiments.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.Thus, the following description and drawings are illustrative and arenot to be construed as limiting. Numerous specific details are describedto provide a thorough understanding of the disclosure. However, incertain instances, well-known or conventional details are not describedin order to avoid obscuring the description. References to one or anembodiment in the present disclosure can be references to the sameembodiment or any embodiment; and, such references mean at least one ofthe embodiments.

Reference to “one embodiment” or “an embodiment” means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment,nor are separate or alternative embodiments mutually exclusive of otherembodiments. Moreover, various features are described which may beexhibited by some embodiments and not by others.

The terms used in this specification generally have their ordinarymeanings in the art, within the context of the disclosure, and in thespecific context where each term is used. Alternative language andsynonyms may be used for any one or more of the terms discussed herein,and no special significance should be placed upon whether or not a termis elaborated or discussed herein. In some cases, synonyms for certainterms are provided. A recital of one or more synonyms does not excludethe use of other synonyms. The use of examples anywhere in thisspecification including examples of any terms discussed herein isillustrative only, and is not intended to further limit the scope andmeaning of the disclosure or of any example term. Likewise, thedisclosure is not limited to various embodiments given in thisspecification.

Without intent to limit the scope of the disclosure, examples ofinstruments, apparatus, methods, and their related results according tothe embodiments of the present disclosure are given below. Note thattitles or subtitles may be used in the examples for convenience of areader, which in no way should limit the scope of the disclosure. Unlessotherwise defined, technical, and scientific terms used herein have themeaning as commonly understood by one of ordinary skill in the art towhich this disclosure pertains. In the case of conflict, the presentdocument, including definitions will control.

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

Overview

Disclosed herein are systems, methods, and computer-readable media foranalyzing memory usage in a network node. According to some aspects ofthe subject technology, a network assurance appliance may be configuredto query a node in the network fabric for a number of hardware levelentries, stored in memory for the node, that are associated with aconcrete level network rule. The network assurance appliance mayidentify a logical level network intent associated with the concretelevel network rule, identify a logical level component of the logicallevel network intent, and attribute the number of hardware level entriesto the logical level component.

Example Embodiments

The disclosed technology addresses the need in the art for analyzingmemory usage in a network node. The present technology will be describedin the following disclosure as follows. The discussion begins with anintroductory discussion of network assurance and a description ofexample computing environments, as illustrated in FIGS. 1A and 1B. Adiscussion of network models for network assurance, as shown in FIGS. 2Athrough 2D, and network assurance systems and methods will then follow.The discussion concludes with a description of an example networkdevice, as illustrated in FIG. 10, and an example computing device, asillustrated in FIG. 11, including example hardware components suitablefor hosting software applications and performing computing operations.The disclosure now turns to an introductory discussion of networkassurance.

Network assurance is the guarantee or determination that the network isbehaving as intended by the network operator and has been configuredproperly (e.g., the network is doing what it is intended to do). Intentcan encompass various network operations, such as bridging, routing,security, service chaining, endpoints, compliance, QoS (Quality ofService), audits, etc. Intent can be embodied in one or more policies,settings, configurations, etc., defined for the network and individualnetwork elements (e.g., switches, routers, applications, resources,etc.). However, often times, the configurations, policies, etc., definedby a network operator are incorrect or not accurately reflected in theactual behavior of the network. For example, a network operatorspecifies a configuration A for one or more types of traffic but laterfinds out that the network is actually applying configuration B to thattraffic or otherwise processing that traffic in a manner that isinconsistent with configuration A. This can be a result of manydifferent causes, such as hardware errors, software bugs, varyingpriorities, configuration conflicts, misconfiguration of one or moresettings, improper rule rendering by devices, unexpected errors orevents, software upgrades, configuration changes, failures, etc. Asanother example, a network operator implements configuration C but oneor more other configurations result in the network behaving in a mannerthat is inconsistent with the intent reflected by the implementation ofconfiguration C. For example, such a situation can result whenconfiguration C conflicts with other configurations in the network.

The approaches herein can provide network assurance by modeling variousaspects of the network and/or performing consistency checks as well asother network assurance checks. The network assurance approaches hereincan be implemented in various types of networks, including a privatenetwork, such as a local area network (LAN); an enterprise network; astandalone or traditional network, such as a data center network; anetwork including a physical or underlay layer and a logical or overlaylayer, such as a virtual extensible LAN (VXLAN) or software-definednetwork (SDN) (e.g., Application Centric Infrastructure (ACI) or VMwareNSX networks); etc.

Network models can be constructed for a network and implemented fornetwork assurance. A network model can provide a representation of oneor more aspects of a network, including, without limitation thenetwork's policies, configurations, requirements, security, routing,topology, applications, hardware, filters, contracts, access controllists, infrastructure, etc. As will be further explained below,different types of models can be generated for a network.

Such models can be implemented to ensure that the behavior of thenetwork will be consistent (or is consistent) with the intended behaviorreflected through specific configurations (e.g., policies, settings,definitions, etc.) implemented by the network operator. Unliketraditional network monitoring, which involves sending and analyzingdata packets and observing network behavior, network assurance can beperformed through modeling without necessarily ingesting packet data ormonitoring traffic or network behavior. This can result in foresight,insight, and hindsight: problems can be prevented before they occur,identified when they occur, and fixed immediately after they occur.

Thus, network assurance can involve modeling properties of the networkto deterministically predict the behavior of the network. The networkcan be determined to be healthy if the model(s) indicate proper behavior(e.g., no inconsistencies, conflicts, errors, etc.). The network can bedetermined to be functional, but not fully healthy, if the modelingindicates proper behavior but some inconsistencies. The network can bedetermined to be non-functional and not healthy if the modelingindicates improper behavior and errors. If inconsistencies or errors aredetected by the modeling, a detailed analysis of the correspondingmodel(s) can allow one or more underlying or root problems to beidentified with great accuracy.

The modeling can consume numerous types of smart events which model alarge amount of behavioral aspects of the network. Smart events canimpact various aspects of the network, such as underlay services,overlay services, tenant connectivity, tenant security, tenant end point(EP) mobility, tenant policy, tenant routing, resources, etc.

Having described various aspects of network assurance, the disclosurenow turns to a discussion of example network environments for networkassurance.

FIG. 1A illustrates example network environments, in accordance withvarious aspects of the subject technology. In particular, FIG. 1Aillustrates a diagram of an example Network Environment 100, such as adata center. The Network Environment 100 can include a Fabric 120 whichcan represent the physical layer or infrastructure (e.g., underlay) ofthe Network Environment 100. Fabric 120 can include Spines 102 (e.g.,spine routers or switches) and Leafs 104 (e.g., leaf routers orswitches) which can be interconnected for routing or switching trafficin the Fabric 120. Spines 102 can interconnect Leafs 104 in the Fabric120, and Leafs 104 can connect the Fabric 120 to an overlay or logicalportion of the Network Environment 100, which can include applicationservices, servers, virtual machines, containers, endpoints, etc. Thus,network connectivity in the Fabric 120 can flow from Spines 102 to Leafs104, and vice versa. The interconnections between Leafs 104 and Spines102 can be redundant (e.g., multiple interconnections) to avoid afailure in routing. In some embodiments, Leafs 104 and Spines 102 can befully connected, such that any given Leaf is connected to each of theSpines 102, and any given Spine is connected to each of the Leafs 104.Leafs 104 can be, for example, top-of-rack (“ToR”) switches, aggregationswitches, gateways, ingress and/or egress switches, provider edgedevices, and/or any other type of routing or switching device.

Leafs 104 can be responsible for routing and/or bridging tenant orcustomer packets and applying network policies or rules. Networkpolicies and rules can be driven by one or more Controllers 116, and/orimplemented or enforced by one or more devices, such as Leafs 104. Leafs104 can connect other elements to the Fabric 120. For example, Leafs 104can connect Servers 106, Hypervisors 108, Virtual Machines (VMs) 110,Applications 112, Network Device 114, etc., with Fabric 120. Suchelements can reside in one or more logical or virtual layers ornetworks, such as an overlay network. In some cases, Leafs 104 canencapsulate and decapsulate packets to and from such elements (e.g.,Servers 106) in order to enable communications throughout NetworkEnvironment 100 and Fabric 120. Leafs 104 can also provide any otherdevices, services, tenants, or workloads with access to Fabric 120. Insome cases, Servers 106 connected to Leafs 104 can similarly encapsulateand decapsulate packets to and from Leafs 104. For example, Servers 106can include one or more virtual switches or routers or tunnel endpointsfor tunneling packets between an overlay or logical layer hosted by, orconnected to, Servers 106 and an underlay layer represented by Fabric120 and accessed via Leafs 104.

Applications 112 can include software applications, services,containers, appliances, functions, service chains, etc. For example,Applications 112 can include a firewall, a database, a content deliverynetwork (CDN) server, an intrusion defense system (IDS) or intrusionprevention system (IPS), a deep packet inspection service, a messagerouter, a virtual switch, etc. An application from Applications 112 canbe distributed, chained, or hosted by multiple endpoints (e.g., Servers106, VMs 110, etc.), or may run or execute entirely from a singleendpoint.

VMs 110 can be virtual machines hosted by Hypervisors 108 or virtualmachine managers running on Servers 106. VMs 110 can include workloadsrunning on a guest operating system on a respective server. Hypervisors108 can provide a layer of software, firmware, and/or hardware thatcreates, manages, and/or runs the VMs 110. Hypervisors 108 can allow VMs110 to share hardware resources on Servers 106, and the hardwareresources on Servers 106 to appear as multiple, separate hardwareplatforms. Moreover, Hypervisors 108 on Servers 106 can host one or moreVMs 110.

In some cases, VMs 110 and/or Hypervisors 108 can be migrated to otherServers 106. Servers 106 can similarly be migrated to other locations inNetwork Environment 100. For example, a server connected to a specificleaf can be changed to connect to a different or additional leaf. Suchconfiguration or deployment changes can involve modifications tosettings, configurations, and policies that are applied to the resourcesbeing migrated as well as other network components.

In some cases, one or more Servers 106, Hypervisors 108, and/or VMs 110can represent or reside in a tenant or customer space. Tenant space caninclude workloads, services, applications, devices, networks, and/orresources that are associated with one or more clients or subscribers.Accordingly, traffic in Network Environment 100 can be routed based onspecific tenant policies, spaces, agreements, configurations, etc.Moreover, addressing can vary between one or more tenants. In someconfigurations, tenant spaces can be divided into logical segmentsand/or networks and separated from logical segments and/or networksassociated with other tenants. Addressing, policy, security, andconfiguration information between tenants can be managed by Controllers116, Servers 106, Leafs 104, etc.

Configurations in Network Environment 100 can be implemented at alogical level, a hardware level (e.g., physical), and/or both. Forexample, configurations can be implemented at a logical and/or hardwarelevel based on endpoint or resource attributes, such as endpoint typesand/or application groups or profiles, through a software-definednetwork (SDN) framework (e.g., Application-Centric Infrastructure (ACI)or VMWARE NSX). To illustrate, one or more administrators can defineconfigurations at a logical level (e.g., application or software level)through Controllers 116, which can implement or propagate suchconfigurations through Network Environment 100. In some examples,Controllers 116 can be Application Policy Infrastructure Controllers(APICs) in an ACI framework. In other examples, Controllers 116 can beone or more management components for associated with other SDNsolutions, such as NSX Managers.

Such configurations can define rules, policies, priorities, protocols,attributes, objects, etc., for routing and/or classifying traffic inNetwork Environment 100. For example, such configurations can defineattributes and objects for classifying and processing traffic based onEndpoint Groups (EPGs), Security Groups (SGs), VM types, bridge domains(BDs), virtual routing and forwarding instances (VRFs), tenants,priorities, firewall rules, etc. Other example network objects andconfigurations are further described below. Traffic policies and rulescan be enforced based on tags, attributes, or other characteristics ofthe traffic, such as protocols associated with the traffic, EPGsassociated with the traffic, SGs associated with the traffic, networkaddress information associated with the traffic, etc. Such policies andrules can be enforced by one or more elements in Network Environment100, such as Leafs 104, Servers 106, Hypervisors 108, Controllers 116,etc. As previously explained, Network Environment 100 can be configuredaccording to one or more particular software-defined network (SDN)solutions, such as CISCO ACI or VMWARE NSX. These example SDN solutionsare briefly described below.

ACI can provide an application-centric or policy-based solution throughscalable distributed enforcement. ACI supports integration of physicaland virtual environments under a declarative configuration model fornetworks, servers, services, security, requirements, etc. For example,the ACI framework implements EPGs, which can include a collection ofendpoints or applications that share common configuration requirements,such as security, QoS, services, etc. Endpoints can be virtual/logicalor physical devices, such as VMs, containers, hosts, or physical serversthat are connected to Network Environment 100. Endpoints can have one ormore attributes such as a VM name, guest OS name, a security tag,application profile, etc. Application configurations can be appliedbetween EPGs, instead of endpoints directly, in the form of contracts.Leafs 104 can classify incoming traffic into different EPGs. Theclassification can be based on, for example, a network segmentidentifier such as a VLAN ID, VXLAN Network Identifier (VNID), NetworkVirtualization using Generic Routing Encapsulation (NVGRE) VirtualSubnet Identifier (VSID), MAC address, IP address, etc.

In some cases, classification in the ACI infrastructure can beimplemented by Application Virtual Switches (AVS), which can run on ahost, such as a server or switch. For example, an AVS can classifytraffic based on specified attributes, and tag packets of differentattribute EPGs with different identifiers, such as network segmentidentifiers (e.g., VLAN ID). Finally, Leafs 104 can tie packets withtheir attribute EPGs based on their identifiers and enforce policies,which can be implemented and/or managed by one or more Controllers 116.Leaf 104 can classify to which EPG the traffic from a host belongs andenforce policies accordingly.

Another example SDN solution is based on VMWARE NSX. With VMWARE NSX,hosts can run a distributed firewall (DFW) which can classify andprocess traffic. Consider a case where three types of VMs, namely,application, database, and web VMs, are put into a single layer-2network segment. Traffic protection can be provided within the networksegment based on the VM type. For example, HTTP traffic can be allowedamong web VMs, and disallowed between a web VM and an application ordatabase VM. To classify traffic and implement policies, VMWARE NSX canimplement security groups, which can be used to group the specific VMs(e.g., web VMs, application VMs, and database VMs). DFW rules can beconfigured to implement policies for the specific security groups. Toillustrate, in the context of the previous example, DFW rules can beconfigured to block HTTP traffic between web, application, and databasesecurity groups.

Returning now to FIG. 1A, Network Environment 100 can deploy differenthosts via Leafs 104, Servers 106, Hypervisors 108, VMs 110, Applications112, and Controllers 116, such as VMWARE ESXi hosts, WINDOWS HYPER-Vhosts, bare metal physical hosts, etc. Network Environment 100 mayinteroperate with a variety of Hypervisors 108, Servers 106 (e.g.,physical and/or virtual servers), SDN orchestration platforms, etc.Network Environment 100 may implement a declarative model to allow itsintegration with application design and holistic network policy.

Controllers 116 can provide centralized access to fabric information,application configuration, resource configuration, application-levelconfiguration modeling for a software-defined network (SDN)infrastructure, integration with management systems or servers, etc.Controllers 116 can form a control plane that interfaces with anapplication plane via northbound APIs and a data plane via southboundAPIs.

As previously noted, Controllers 116 can define and manageapplication-level model(s) for configurations in Network Environment100. In some cases, application or device configurations can also bemanaged and/or defined by other components in the network. For example,a hypervisor or virtual appliance, such as a VM or container, can run aserver or management tool to manage software and services in NetworkEnvironment 100, including configurations and settings for virtualappliances.

As illustrated above, Network Environment 100 can include one or moredifferent types of SDN solutions, hosts, etc. For the sake of clarityand explanation purposes, various examples in the disclosure will bedescribed with reference to an ACI framework, and Controllers 116 may beinterchangeably referenced as controllers, APICs, or APIC controllers.However, it should be noted that the technologies and concepts hereinare not limited to ACI solutions and may be implemented in otherarchitectures and scenarios, including other SDN solutions as well asother types of networks which may not deploy an SDN solution.

Further, as referenced herein, the term “hosts” can refer to Servers 106(e.g., physical or logical), Hypervisors 108, VMs 110, containers (e.g.,Applications 112), etc., and can run or include any type of server orapplication solution. Non-limiting examples of “hosts” can includevirtual switches or routers, such as distributed virtual switches (DVS),application virtual switches (AVS), vector packet processing (VPP)switches; VCENTER and NSX MANAGERS; bare metal physical hosts; HYPER-Vhosts; VMs; DOCKER Containers; etc.

FIG. 1B illustrates example network environments, in accordance withvarious aspects of the subject technology. In particular, FIG. 1Billustrates another example of Network Environment 100. In this example,Network Environment 100 includes Endpoints 122 connected to Leafs 104 inFabric 120. Endpoints 122 can be physical and/or logical or virtualentities, such as servers, clients, VMs, hypervisors, softwarecontainers, applications, resources, network devices, workloads, etc.For example, an Endpoint 122 can be an object that represents a physicaldevice (e.g., server, client, switch, etc.), an application (e.g., webapplication, database application, etc.), a logical or virtual resource(e.g., a virtual switch, a virtual service appliance, a virtualizednetwork function (VNF), a VM, a service chain, etc.), a containerrunning a software resource (e.g., an application, an appliance, a VNF,a service chain, etc.), storage, a workload or workload engine, etc.Endpoints 122 can have an address (e.g., an identity), a location (e.g.,host, network segment, virtual routing and forwarding (VRF) instance,domain, etc.), one or more attributes (e.g., name, type, version, patchlevel, OS name, OS type, etc.), a tag (e.g., security tag), a profile,etc.

Endpoints 122 can be associated with respective Logical Groups 118.Logical Groups 118 can be logical entities containing endpoints(physical and/or logical or virtual) grouped together according to oneor more attributes, such as endpoint type (e.g., VM type, workload type,application type, etc.), one or more requirements (e.g., policyrequirements, security requirements, QoS requirements, customerrequirements, resource requirements, etc.), a resource name (e.g., VMname, application name, etc.), a profile, platform or operating system(OS) characteristics (e.g., OS type or name including guest and/or hostOS, etc.), an associated network or tenant, one or more policies, a tag,etc. For example, a logical group can be an object representing acollection of endpoints grouped together. To illustrate, Logical Group 1can contain client endpoints, Logical Group 2 can contain web serverendpoints, Logical Group 3 can contain application server endpoints,Logical Group N can contain database server endpoints, etc. In someexamples, Logical Groups 118 are EPGs in an ACI environment and/or otherlogical groups (e.g., SGs) in another SDN environment.

Traffic to and/or from Endpoints 122 can be classified, processed,managed, etc., based Logical Groups 118. For example, Logical Groups 118can be used to classify traffic to or from Endpoints 122, apply policiesto traffic to or from Endpoints 122, define relationships betweenEndpoints 122, define roles of Endpoints 122 (e.g., whether an endpointconsumes or provides a service, etc.), apply rules to traffic to or fromEndpoints 122, apply filters or access control lists (ACLs) to trafficto or from Endpoints 122, define communication paths for traffic to orfrom Endpoints 122, enforce requirements associated with Endpoints 122,implement security and other configurations associated with Endpoints122, etc.

In an ACI environment, Logical Groups 118 can be EPGs used to definecontracts in the ACI. Contracts can include rules specifying what andhow communications between EPGs take place. For example, a contract candefine what provides a service, what consumes a service, and what policyobjects are related to that consumption relationship. A contract caninclude a policy that defines the communication path and all relatedelements of a communication or relationship between endpoints or EPGs.For example, a Web EPG can provide a service that a Client EPG consumes,and that consumption can be subject to a filter (ACL) and a servicegraph that includes one or more services, such as firewall inspectionservices and server load balancing.

FIG. 2A illustrates an example object model for a network, in accordancewith various aspects of the subject technology. In particular, FIG. 2Aillustrates a diagram of an example Management Information Model 200 foran SDN network, such as Network Environment 100. The followingdiscussion of Management Information Model 200 references various termswhich shall also be used throughout the disclosure. Accordingly, forclarity, the disclosure shall first provide below a list of terminology,which will be followed by a more detailed discussion of ManagementInformation Model 200.

As used herein, an “Alias” can refer to a changeable name for a givenobject. Thus, even if the name of an object, once created, cannot bechanged, the Alias can be a field that can be changed.

As used herein, the term “Aliasing” can refer to a rule (e.g.,contracts, policies, configurations, etc.) that overlaps one or moreother rules. For example, Contract 1 defined in a logical model of anetwork can be said to be aliasing Contract 2 defined in the logicalmodel of the network if Contract 1 overlaps Contract 1. In this example,by aliasing Contract 2, Contract 1 may render Contract 2 redundant orinoperable. For example, if Contract 1 has a higher priority thanContract 2, such aliasing can render Contract 2 redundant based onContract 1's overlapping and higher priority characteristics.

As used herein, the term “APIC” can refer to one or more controllers(e.g., Controllers 116) in an ACI framework. The APIC can provide aunified point of automation and management, policy programming,application deployment, health monitoring for an ACI multitenant fabric.The APIC can be implemented as a single controller, a distributedcontroller, or a replicated, synchronized, and/or clustered controller.

As used herein, the term “BDD” can refer to a binary decision tree. Abinary decision tree can be a data structure representing functions,such as Boolean functions.

As used herein, the term “BD” can refer to a bridge domain. A bridgedomain can be a set of logical ports that share the same flooding orbroadcast characteristics. Like a virtual LAN (VLAN), bridge domains canspan multiple devices. A bridge domain can be a L2 (Layer 2) construct.

As used herein, a “Consumer” can refer to an endpoint, resource, and/orEPG that consumes a service.

As used herein, a “Context” can refer to an L3 (Layer 3) address domainthat allows multiple instances of a routing table to exist and worksimultaneously. This increases functionality by allowing network pathsto be segmented without using multiple devices. Non-limiting examples ofa context or L3 address domain can include a Virtual Routing andForwarding (VRF) instance, a private network, and so forth.

As used herein, the term “Contract” can refer to rules or configurationsthat specify what and how communications in a network are conducted(e.g., allowed, denied, filtered, processed, etc.). In an ACI network,contracts can specify how communications between endpoints and/or EPGstake place. In some examples, a contract can provide rules andconfigurations akin to an Access Control List (ACL).

As used herein, the term “Distinguished Name” (DN) can refer to a uniquename that describes an object, such as an MO, and locates its place inManagement Information Model 200. In some cases, the DN can be (orequate to) a Fully Qualified Domain Name (FQDN).

As used herein, the term “Endpoint Group” (EPG) can refer to a logicalentity or object associated with a collection or group of endpoints aspreviously described with reference to FIG. 1B.

As used herein, the term “Filter” can refer to a parameter orconfiguration for allowing communications. For example, in a whitelistmodel where all communications are blocked by default, a communicationmust be given explicit permission to prevent such communication frombeing blocked. A filter can define permission(s) for one or morecommunications or packets. A filter can thus function similar to an ACLor Firewall rule. In some examples, a filter can be implemented in apacket (e.g., TCP/IP) header field, such as L3 protocol type, L4 (Layer4) ports, and so on, which is used to allow inbound or outboundcommunications between endpoints or EPGs, for example.

As used herein, the term “L2 Out” can refer to a bridged connection. Abridged connection can connect two or more segments of the same networkso that they can communicate. In an ACI framework, an L2 out can be abridged (Layer 2) connection between an ACI fabric (e.g., Fabric 120)and an outside Layer 2 network, such as a switch.

As used herein, the term “L3 Out” can refer to a routed connection. Arouted Layer 3 connection uses a set of protocols that determine thepath that data follows in order to travel across networks from itssource to its destination. Routed connections can perform forwarding(e.g., IP forwarding) according to a protocol selected, such as BGP(border gateway protocol), OSPF (Open Shortest Path First), EIGRP(Enhanced Interior Gateway Routing Protocol), etc.

As used herein, the term “Managed Object” (MO) can refer to an abstractrepresentation of objects that are managed in a network (e.g., NetworkEnvironment 100). The objects can be concrete objects (e.g., a switch,server, adapter, etc.), or logical objects (e.g., an applicationprofile, an EPG, a fault, etc.). The MOs can be network resources orelements that are managed in the network. For example, in an ACIenvironment, an MO can include an abstraction of an ACI fabric (e.g.,Fabric 120) resource.

As used herein, the term “Management Information Tree” (MIT) can referto a hierarchical management information tree containing the MOs of asystem. For example, in ACI, the MIT contains the MOs of the ACI fabric(e.g., Fabric 120). The MIT can also be referred to as a ManagementInformation Model (MIM), such as Management Information Model 200.

As used herein, the term “Policy” can refer to one or morespecifications for controlling some aspect of system or networkbehavior. For example, a policy can include a named entity that containsspecifications for controlling some aspect of system behavior. Toillustrate, a Layer 3 Outside Network Policy can contain the BGPprotocol to enable BGP routing functions when connecting Fabric 120 toan outside Layer 3 network.

As used herein, the term “Profile” can refer to the configurationdetails associated with a policy. For example, a profile can include anamed entity that contains the configuration details for implementingone or more instances of a policy. To illustrate, a switch node profilefor a routing policy can contain the switch-specific configurationdetails to implement the BGP routing protocol.

As used herein, the term “Provider” refers to an object or entityproviding a service. For example, a provider can be an EPG that providesa service.

As used herein, the term “Subject” refers to one or more parameters in acontract for defining communications. For example, in ACI, subjects in acontract can specify what information can be communicated and how.Subjects can function similar to ACLs.

As used herein, the term “Tenant” refers to a unit of isolation in anetwork. For example, a tenant can be a secure and exclusive virtualcomputing environment. In ACI, a tenant can be a unit of isolation froma policy perspective, but does not necessarily represent a privatenetwork. Indeed, ACI tenants can contain multiple private networks(e.g., VRFs). Tenants can represent a customer in a service providersetting, an organization or domain in an enterprise setting, or just agrouping of policies.

As used herein, the term “VRF” refers to a virtual routing andforwarding instance. The VRF can define a Layer 3 address domain thatallows multiple instances of a routing table to exist and worksimultaneously. This increases functionality by allowing network pathsto be segmented without using multiple devices. Also known as a contextor private network.

Having described various terms used herein, the disclosure now returnsto a discussion of Management Information Model (MIM) 200 in FIG. 2A. Aspreviously noted, MIM 200 can be a hierarchical management informationtree or MIT. Moreover, MIM 200 can be managed and processed byControllers 116, such as APICs in an ACI. Controllers 116 can enable thecontrol of managed resources by presenting their manageablecharacteristics as object properties that can be inherited according tothe location of the object within the hierarchical structure of themodel.

The hierarchical structure of MIM 200 starts with Policy Universe 202 atthe top (Root) and contains parent and child nodes 116, 204, 206, 208,210, 212. Nodes 116, 202, 204, 206, 208, 210, 212 in the tree representthe managed objects (MOs) or groups of objects. Each object in thefabric (e.g., Fabric 120) has a unique distinguished name (DN) thatdescribes the object and locates its place in the tree. The Nodes 116,202, 204, 206, 208, 210, 212 can include the various MOs, as describedbelow, which contain policies that govern the operation of the system.

Controllers 116

Controllers 116 (e.g., APIC controllers) can provide management, policyprogramming, application deployment, and health monitoring for Fabric120.

Node 204

Node 204 includes a tenant container for policies that enable anadministrator to exercise domain-based access control. Non-limitingexamples of tenants can include:

User tenants defined by the administrator according to the needs ofusers. They contain policies that govern the operation of resources suchas applications, databases, web servers, network-attached storage,virtual machines, and so on.

The common tenant is provided by the system but can be configured by theadministrator. It contains policies that govern the operation ofresources accessible to all tenants, such as firewalls, load balancers,Layer 4 to Layer 7 services, intrusion detection appliances, and so on.

The infrastructure tenant is provided by the system but can beconfigured by the administrator. It contains policies that govern theoperation of infrastructure resources such as the fabric overlay (e.g.,VXLAN). It also enables a fabric provider to selectively deployresources to one or more user tenants. Infrastructure tenant polices canbe configurable by the administrator.

The management tenant is provided by the system but can be configured bythe administrator. It contains policies that govern the operation offabric management functions used for in-band and out-of-bandconfiguration of fabric nodes. The management tenant contains a privateout-of-bound address space for the Controller/Fabric internalcommunications that is outside the fabric data path that provides accessthrough the management port of the switches. The management tenantenables discovery and automation of communications with virtual machinecontrollers.

Node 206

Node 206 can contain access policies that govern the operation of switchaccess ports that provide connectivity to resources such as storage,compute, Layer 2 and Layer 3 (bridged and routed) connectivity, virtualmachine hypervisors, Layer 4 to Layer 7 devices, and so on. If a tenantrequires interface configurations other than those provided in thedefault link, Cisco Discovery Protocol (CDP), Link Layer DiscoveryProtocol (LLDP), Link Aggregation Control Protocol (LACP), or SpanningTree Protocol (STP), an administrator can configure access policies toenable such configurations on the access ports of Leafs 104.

Node 206 can contain fabric policies that govern the operation of theswitch fabric ports, including such functions as Network Time Protocol(NTP) server synchronization, Intermediate System-to-Intermediate SystemProtocol (IS-IS), Border Gateway Protocol (BGP) route reflectors, DomainName System (DNS) and so on. The fabric MO contains objects such aspower supplies, fans, chassis, and so on.

Node 208

Node 208 can contain VM domains that group VM controllers with similarnetworking policy requirements. VM controllers can share virtual space(e.g., VLAN or VXLAN space) and application EPGs. Controllers 116communicate with the VM controller to publish network configurationssuch as port groups that are then applied to the virtual workloads.

Node 210

Node 210 can contain Layer 4 to Layer 7 service integration life cycleautomation framework that enables the system to dynamically respond whena service comes online or goes offline. Policies can provide servicedevice package and inventory management functions.

Node 212

Node 212 can contain access, authentication, and accounting (AAA)policies that govern user privileges, roles, and security domains ofFabric 120.

The hierarchical policy model can fit well with an API, such as a RESTAPI interface. When invoked, the API can read from or write to objectsin the MIT. URLs can map directly into distinguished names that identifyobjects in the MIT. Data in the MIT can be described as a self-containedstructured tree text document encoded in XML or JSON, for example.

FIG. 2B illustrates an example object model for a tenant object, inaccordance with various aspects of the subject technology. FIG. 2Bincludes an example object model 220 for a tenant portion of MIM 200. Aspreviously noted, a tenant is a logical container for applicationpolicies that enable an administrator to exercise domain-based accesscontrol. A tenant thus represents a unit of isolation from a policyperspective, but it does not necessarily represent a private network.Tenants can represent a customer in a service provider setting, anorganization, or domain in an enterprise setting, or just a convenientgrouping of policies. Moreover, tenants can be isolated from one anotheror can share resources.

Tenant portion 204A of MIM 200 can include various entities, and theentities in Tenant Portion 204A can inherit policies from parententities. Non-limiting examples of entities in Tenant Portion 204A caninclude Filters 240, Contracts 236, Outside Networks 222, Bridge Domains230, VRF Instances 234, and Application Profiles 224.

Bridge Domains 230 can include Subnets 232. Contracts 236 can includeSubjects 238. Application Profiles 224 can contain one or more EPGs 226.Some applications can contain multiple components. For example, ane-commerce application could require a web server, a database server,data located in a storage area network, and access to outside resourcesthat enable financial transactions. Application Profile 224 contains asmany (or as few) EPGs as necessary that are logically related toproviding the capabilities of an application.

EPG 226 can be organized in various ways, such as based on theapplication they provide, the function they provide (such asinfrastructure), where they are in the structure of the data center(such as DMZ), or whatever organizing principle that a fabric or tenantadministrator chooses to use.

EPGs in the fabric can contain various types of EPGs, such asapplication EPGs, Layer 2 external outside network instance EPGs, Layer3 external outside network instance EPGs, management EPGs forout-of-band or in-band access, etc. EPGs 226 can also contain Attributes228, such as encapsulation-based EPGs, IP-based EPGs, or MAC-based EPGs.

As previously mentioned, EPGs can contain endpoints (e.g., EPs 122) thathave common characteristics or attributes, such as common policyrequirements (e.g., security, virtual machine mobility (VMM), QoS, orLayer 4 to Layer 7 services). Rather than configure and manage endpointsindividually, they can be placed in an EPG and managed as a group.

Policies apply to EPGs, including the endpoints they contain. An EPG canbe statically configured by an administrator in Controllers 116, ordynamically configured by an automated system such as VCENTER orOPENSTACK.

To activate tenant policies in Tenant Portion 204A, fabric accesspolicies should be configured and associated with tenant policies.Access policies enable an administrator to configure other networkconfigurations, such as port channels and virtual port channels,protocols such as LLDP, CDP, or LACP, and features such as monitoring ordiagnostics.

FIG. 2C illustrates an example association of various objects, inaccordance with various aspects of the subject technology. Inparticular, FIG. 2C includes an example Association 260 of tenantentities and access entities in MIM 200. Policy Universe 202 containsTenant Portion 204A and Access Portion 206A. Thus, Tenant Portion 204Aand Access Portion 206A are associated through Policy Universe 202.

Access Portion 206A can contain fabric and infrastructure accesspolicies. Typically, in a policy model, EPGs are coupled with VLANs. Fortraffic to flow, an EPG is deployed on a leaf port with a VLAN in aphysical, VMM, L2 out, L3 out, or Fiber Channel domain, for example.

Access Portion 206A thus contains Domain Profile 236 which can define aphysical, VMM, L2 out, L3 out, or Fiber Channel domain, for example, tobe associated to the EPGs. Domain Profile 236 contains VLAN InstanceProfile 238 (e.g., VLAN pool) and Attacheable Access Entity Profile(AEP) 240, which are associated directly with application EPGs. The AEP240 deploys the associated application EPGs to the ports to which it isattached, and automates the task of assigning VLANs. While a large datacenter can have thousands of active VMs provisioned on hundreds ofVLANs, Fabric 120 can automatically assign VLAN IDs from VLAN pools.This saves time compared with trunking down VLANs in a traditional datacenter.

FIG. 2D illustrates a schematic diagram of example models forimplementing MIM 200. The network assurance models can include L_Model270A (Logical Model), LR_Model 270B (Logical Rendered Model or LogicalRuntime Model), Li_Model 272 (Logical Model for i), Ci_Model 274(Concrete model for i), and Hi_Model 276 (Hardware model or TCAM Modelfor i).

L_Model 270A is the logical representation of the objects and theirrelationships in MIM 200. L_Model 270A can be generated by Controllers116 based on configurations entered in Controllers 116 for the network,and thus represents the configurations of the network at Controllers116. This is the declaration of the “end-state” expression that isdesired when the elements of the network entities (e.g., applications)are connected and Fabric 120 is provisioned by Controllers 116. In otherwords, because L_Model 270A represents the configurations entered inControllers 116, including the objects and relationships in MIM 200, itcan also reflect the “intent” of the administrator: how theadministrator wants the network and network elements to behave.

LR_Model 270B is the abstract model expression that Controllers 116(e.g., APICs in ACI) resolve from L_Model 270A. LR_Model 270B can thusprovide the elemental configuration components that would be deliveredto the physical infrastructure (e.g., Fabric 120) to execute one or morepolicies. For example, LR_Model 270B can be delivered to Leafs 104 inFabric 120 to configure Leafs 104 for communication with attachedEndpoints 122.

Li_Model 272 is a switch-level or switch-specific model obtained fromLogical Model 270A and/or Resolved Model 270B. For example, Li_Model 272can represent the portion of L_Model 270A and/or LR_Model 270Bpertaining to a specific switch or router i. To illustrate, Li_Model 272L₁ can represent the portion of L_Model 270A and/or LR_Model 270Bpertaining to Leaf 1 (104). Thus, Li_Model 272 can be generated fromL_Model 270A and/or LR_Model 270B for one or more switch or routers(e.g., Leafs 104 and/or Spines 102) on Fabric 120.

Ci_Model 274 is the actual in-state configuration at the individualfabric member i (e.g., switch i). In other words, Ci_Model 274 is aswitch-level or switch-specific model that is based on Li_Model 272. Forexample, Controllers 116 can deliver Li_Model 272 to Leaf 1 (104). Leaf1 (104) can take Li_Model 272, which can be specific to Leaf 1 (104),and render the policies in Li_Model 272 into a concrete model, Ci_Model274, that runs on Leaf 1 (104). Leaf 1 (104) can render Li_Model 272 viathe OS on Leaf 1 (104), for example. Thus, Ci_Model 274 can be analogousto compiled software, as it is the form of Li_Model 272 that the switchOS at Leaf 1 (104) can execute.

Hi_Model 276 is also a switch-level or switch-specific model for switchi, but is based on Ci_Model 274 for switch i. Hi_Model 276 is the actualconfiguration (e.g., rules) stored or rendered on the hardware or memory(e.g., TCAM memory) at the individual fabric member i (e.g., switch i).For example, Hi_Model 276 can represent the configurations (e.g., rules)which Leaf 1 (104) stores or renders on the hardware (e.g., TCAM memory)of Leaf 1 (104) based on Ci_Model 274 at Leaf 1 (104). The switch OS atLeaf 1 (104) can render or execute Ci_Model 274, and Leaf 1 (104) canstore or render the configurations from Ci Model in storage, such as thememory or TCAM at Leaf 1 (104). The configurations from Hi_Model 276stored or rendered by Leaf 1 (104) represent the configurations thatwill be implemented by Leaf 1 (104) when processing traffic.

While Models 272, 274, 276 are shown as device-specific models, similarmodels can be generated or aggregated for a collection of fabric members(e.g., Leafs 104 and/or Spines 102) in Fabric 120. When combined,device-specific models, such as Model 272, Model 274, and/or Model 276,can provide a representation of Fabric 120 that extends beyond aparticular device. For example, in some cases, Li_Model 272, Ci Model272, and/or Hi Model 272 associated with some or all individual fabricmembers (e.g., Leafs 104 and Spines 102) can be combined or aggregatedto generate one or more aggregated models based on the individual fabricmembers.

As referenced herein, the terms H Model, T Model, and TCAM Model can beused interchangeably to refer to a hardware model, such as Hi_Model 276.For example, Ti Model, Hi Model and TCAMi Model may be usedinterchangeably to refer to Hi_Model 276.

Models 270A, 270B, 272, 274, 276 can provide representations of variousaspects of the network or various configuration stages for MIM 200. Forexample, one or more of Models 270A, 270B, 272, 274, 276 can be used togenerate Underlay Model 278 representing one or more aspects of Fabric120 (e.g., underlay topology, routing, etc.), Overlay Model 280representing one or more aspects of the overlay or logical segment(s) ofNetwork Environment 100 (e.g., COOP, MPBGP, tenants, VRFs, VLANs,VXLANs, virtual applications, VMs, hypervisors, virtual switching,etc.), Tenant Model 282 representing one or more aspects of Tenantportion 204A in MIM 200 (e.g., security, forwarding, service chaining,QoS, VRFs, BDs, Contracts, Filters, EPGs, subnets, etc.), ResourcesModel 284 representing one or more resources in Network Environment 100(e.g., storage, computing, VMs, port channels, physical elements, etc.),etc.

In general, L_Model 270A can be the high-level expression of what existsin the LR_Model 270B, which should be present on the concrete devices asCi_Model 274 and Hi_Model 276 expression. If there is any gap betweenthe models, there may be inconsistent configurations or problems.

FIG. 3A illustrates a diagram of an example Assurance Appliance 300 fornetwork assurance. In this example, Assurance Appliance 300 can includek VMs 110 operating in cluster mode. VMs are used in this example forexplanation purposes. However, it should be understood that otherconfigurations are also contemplated herein, such as use of containers,bare metal devices, Endpoints 122, or any other physical or logicalsystems. Moreover, while FIG. 3A illustrates a cluster modeconfiguration, other configurations are also contemplated herein, suchas a single mode configuration (e.g., single VM, container, or server)or a service chain for example.

Assurance Appliance 300 can run on one or more Servers 106, VMs 110,Hypervisors 108, EPs 122, Leafs 104, Controllers 116, or any othersystem or resource. For example, Assurance Appliance 300 can be alogical service or application running on one or more VMs 110 in NetworkEnvironment 100.

The Assurance Appliance 300 can include Data Framework 308, which can bebased on, for example, APACHE APEX and HADOOP. In some cases, assurancechecks can be written as individual operators that reside in DataFramework 308. This enables a natively horizontal scale-out architecturethat can scale to arbitrary number of switches in Fabric 120 (e.g., ACIfabric).

Assurance Appliance 300 can poll Fabric 120 at a configurableperiodicity (e.g., an epoch). The analysis workflow can be setup as aDAG (Directed Acyclic Graph) of Operators 310, where data flows from oneoperator to another and eventually results are generated and persistedto Database 302 for each interval (e.g., each epoch).

The north-tier implements API Server (e.g., APACHE Tomcat and Springframework) 304 and Web Server 306. A graphical user interface (GUI)interacts via the APIs exposed to the customer. These APIs can also beused by the customer to collect data from Assurance Appliance 300 forfurther integration into other tools.

Operators 310 in Data Framework 308 (e.g., APEX/Hadoop) can togethersupport assurance operations. Below are non-limiting examples ofassurance operations that can be performed by Assurance Appliance 300via Operators 310.

Security Policy Adherence

Assurance Appliance 300 can check to make sure the configurations orspecification from L_Model 270A, which may reflect the user's intent forthe network, including for example the security policies andcustomer-configured contracts, are correctly implemented and/or renderedin Li_Model 272, Ci_Model 274, and Hi_Model 276, and thus properlyimplemented and rendered by the fabric members (e.g., Leafs 104), andreport any errors, contract violations, or irregularities found.

Static Policy Analysis

Assurance Appliance 300 can check for issues in the specification of theuser's intent or intents (e.g., identify contradictory or conflictingpolicies in L_Model 270A).

TCAM Utilization

TCAM is a scarce resource in the fabric (e.g., Fabric 120). However,Assurance Appliance 300 can analyze the TCAM utilization by the networkdata (e.g., Longest Prefix Match (LPM) tables, routing tables, VLANtables, BGP updates, etc.), Contracts, Logical Groups 118 (e.g., EPGs),Tenants, Spines 102, Leafs 104, and other dimensions in NetworkEnvironment 100 and/or objects in MIM 200, to provide a network operatoror user visibility into the utilization of this scarce resource. Thiscan greatly help for planning and other optimization purposes.

Endpoint Checks

Assurance Appliance 300 can validate that the fabric (e.g., fabric 120)has no inconsistencies in the Endpoint information registered (e.g., twoleafs announcing the same endpoint, duplicate subnets, etc.), amongother such checks.

Tenant Routing Checks

Assurance Appliance 300 can validate that BDs, VRFs, subnets (bothinternal and external), VLANs, contracts, filters, applications, EPGs,etc., are correctly programmed.

Infrastructure Routing

Assurance Appliance 300 can validate that infrastructure routing (e.g.,IS-IS protocol) has no convergence issues leading to black holes, loops,flaps, and other problems.

MP-BGP Route Reflection Checks

The network fabric (e.g., Fabric 120) can interface with other externalnetworks and provide connectivity to them via one or more protocols,such as Border Gateway Protocol (BGP), Open Shortest Path First (OSPF),etc. The learned routes are advertised within the network fabric via,for example, MP-BGP. These checks can ensure that a route reflectionservice via, for example, MP-BGP (e.g., from Border Leaf) does not havehealth issues.

Logical Lint and Real-time Change Analysis

Assurance Appliance 300 can validate rules in the specification of thenetwork (e.g., L_Model 270A) are complete and do not haveinconsistencies or other problems. MOs in the MIM 200 can be checked byAssurance Appliance 300 through syntactic and semantic checks performedon L_Model 270A and/or the associated configurations of the MOs in MIM200. Assurance Appliance 300 can also verify that unnecessary, stale,unused or redundant configurations, such as contracts, are removed.

FIG. 3B illustrates an architectural diagram of an example system 350for network assurance. In some cases, system 350 can correspond to theDAG of Operators 310 previously discussed with respect to FIG. 3A Inthis example, Topology Explorer 312 communicates with Controllers 116(e.g., APIC controllers) in order to discover or otherwise construct acomprehensive topological view of Fabric 120 (e.g., Spines 102, Leafs104, Controllers 116, Endpoints 122, and any other components as well astheir interconnections). While various architectural components arerepresented in a singular, boxed fashion, it is understood that a givenarchitectural component, such as Topology Explorer 312, can correspondto one or more individual Operators 310 and may include one or morenodes or endpoints, such as one or more servers, VMs, containers,applications, service functions (e.g., functions in a service chain orvirtualized network function), etc.

Topology Explorer 312 is configured to discover nodes in Fabric 120,such as Controllers 116, Leafs 104, Spines 102, etc. Topology Explorer312 can additionally detect a majority election performed amongstControllers 116, and determine whether a quorum exists amongstControllers 116. If no quorum or majority exists, Topology Explorer 312can trigger an event and alert a user that a configuration or othererror exists amongst Controllers 116 that is preventing a quorum ormajority from being reached. Topology Explorer 312 can detect Leafs 104and Spines 102 that are part of Fabric 120 and publish theircorresponding out-of-band management network addresses (e.g., IPaddresses) to downstream services. This can be part of the topologicalview that is published to the downstream services at the conclusion ofTopology Explorer's 312 discovery epoch (e.g., 5 minutes, or some otherspecified interval).

Unified Collector 314 can receive the topological view from TopologyExplorer 312 and use the topology information to collect information fornetwork assurance from Fabric 120. Such information can include L_Model270A and/or LR_Model 270B from Controllers 116, switch softwareconfigurations (e.g., Ci_Model 274) from Leafs 104 and/or Spines 102,hardware configurations (e.g., Hi_Model 276) from Leafs 104 and/orSpines 102, etc. Unified Collector 314 can collect Ci Model 274 and HiModel 276 from individual fabric members (e.g., Leafs 104 and Spines102).

Unified Collector 314 can poll the devices that Topology Explorer 312discovers in order to collect data from Fabric 120 (e.g., from theconstituent members of the fabric). Unified Collector 314 can collectthe data using interfaces exposed by Controller 116 and/or switchsoftware (e.g., switch OS), including, for example, a RepresentationState Transfer (REST) Interface and a Secure Shell (SSH) Interface.

In some cases, Unified Collector 314 collects L_Model 270A, LR_Model270B, and/or Ci_Model 274 via a REST API, and the hardware information(e.g., configurations, tables, fabric card information, rules, routes,etc.) via SSH using utilities provided by the switch software, such asvirtual shell (VSH or VSHELL) for accessing the switch command-lineinterface (CLI) or VSH_LC shell for accessing runtime state of the linecard.

Unified Collector 314 can poll other information from Controllers 116,including: topology information, tenant forwarding/routing information,tenant security policies, contracts, interface policies, physical domainor VMM domain information, OOB (out-of-band) management IP's of nodes inthe fabric, etc.

Unified Collector 314 can also poll other information from Leafs 104 andSpines 102, such as: Ci Models 274 for VLANs, BDs, security policies,Link Layer Discovery Protocol (LLDP) connectivity information of Leafs104 and/or Spines 102, endpoint information from EPM/COOP, fabric cardinformation from Spines 102, routing information base (RIB) tables,forwarding information base (FIB) tables from Leafs 104 and/or Spines102, security group hardware tables (e.g., TCAM tables) from switches,etc.

Assurance Appliance 300 can run one or more instances of UnifiedCollector 314. For example, Assurance Appliance 300 can run one, two,three, or more instances of Unified Collector 314. The task of datacollecting for each node in the topology (e.g., Fabric 120 includingSpines 102, Leafs 104, Controllers 116, etc.) can be sharded or loadbalanced, to a unique instance of Unified Collector 314. Data collectionacross the nodes can thus be performed in parallel by one or moreinstances of Unified Collector 314. Within a given node, commands anddata collection can be executed serially. Assurance Appliance 300 cancontrol the number of threads used by each instance of Unified Collector314 to poll data from Fabric 120.

Data collected by Unified Collector 314 can be compressed and sent todownstream services. In some examples, Unified Collector 314 can collectdata in an online fashion or real-time fashion, and send the datadownstream, as it is collected, for further analysis. In some examples,Unified Collector 314 can collect data in an offline fashion, andcompile the data for later analysis or transmission.

Assurance Appliance 300 can contact Controllers 116, Spines 102, Leafs104, and other nodes to collect various types of data. In somescenarios, Assurance Appliance 300 may experience a failure (e.g.,connectivity problem, hardware or software error, etc.) that prevents itfrom being able to collect data for a period of time. AssuranceAppliance 300 can handle such failures seamlessly, and generate eventsbased on such failures.

Switch Logical Policy Generator 316 can receive L_Model 270A and/orLR_Model 270B from Unified Collector 314 and calculate Li_Model 272 foreach network device i (e.g., switch i) in Fabric 120. For example,Switch Logical Policy Generator 316 can receive L_Model 270A and/orLR_Model 270B and generate Li_Model 272 by projecting a logical modelfor each individual node i (e.g., Spines 102 and/or Leafs 104) in Fabric120. Switch Logical Policy Generator 316 can generate Li_Model 272 foreach switch in Fabric 120, thus creating a switch logical model based onL_Model 270A for each switch.

Switch Logical Configuration Generator 316 can also perform changeanalysis and generate lint events or records for problems discovered inL_Model 270A and/or LR_Model 270B. The lint events or records can beused to generate alerts for a user or network operator.

Policy Operator 318 can receive Ci_Model 274 and Hi_Model 276 for eachswitch from Unified Collector 314, and Li_Model 272 for each switch fromSwitch Logical Policy Generator 316, and perform assurance checks andanalysis (e.g., security adherence checks, TCAM utilization analysis,etc.) based on Ci_Model 274, Hi_Model 276, and Li_Model 272. PolicyOperator 318 can perform assurance checks on a switch-by-switch basis bycomparing one or more of the models.

Returning to Unified Collector 314, Unified Collector 314 can also sendL_Model 270A and/or LR_Model 270B to Routing Policy Parser 320, andCi_Model 274 and Hi_Model 276 to Routing Parser 326.

Routing Policy Parser 320 can receive L_Model 270A and/or LR_Model 270Band parse the model(s) for information that may be relevant todownstream operators, such as Endpoint Checker 322 and Tenant RoutingChecker 324. Similarly, Routing Parser 326 can receive Ci_Model 274 andHi_Model 276 and parse each model for information for downstreamoperators, Endpoint Checker 322 and Tenant Routing Checker 324.

After Ci_Model 274, Hi_Model 276, L_Model 270A and/or LR_Model 270B areparsed, Routing Policy Parser 320 and/or Routing Parser 326 can sendcleaned-up protocol buffers (Proto Buffs) to the downstream operators,Endpoint Checker 322 and Tenant Routing Checker 324. Endpoint Checker322 can then generate events related to Endpoint violations, such asduplicate IPs, APIPA, etc., and Tenant Routing Checker 324 can generateevents related to the deployment of BDs, VRFs, subnets, routing tableprefixes, etc.

FIG. 3C illustrates a schematic diagram of an example system for staticpolicy analysis in a network (e.g., Network Environment 100). StaticPolicy Analyzer 360 can perform assurance checks to detect configurationviolations, logical lint events, contradictory or conflicting policies,unused contracts, incomplete configurations, etc. Static Policy Analyzer360 can check the specification of the user's intent or intents inL_Model 270A to determine if any configurations in Controllers 116 areinconsistent with the specification of the user's intent or intents.

Static Policy Analyzer 360 can include one or more of the Operators 310executed or hosted in Assurance Appliance 300. However, in otherconfigurations, Static Policy Analyzer 360 can run one or more operatorsor engines that are separate from Operators 310 and/or AssuranceAppliance 300. For example, Static Policy Analyzer 360 can be a VM, acluster of VMs, or a collection of endpoints in a service functionchain.

Static Policy Analyzer 360 can receive as input L_Model 270A fromLogical Model Collection Process 366 and Rules 368 defined for eachfeature (e.g., object) in L_Model 270A. Rules 368 can be based onobjects, relationships, definitions, configurations, and any otherfeatures in MIM 200. Rules 368 can specify conditions, relationships,parameters, and/or any other information for identifying configurationviolations or issues.

Moreover, Rules 368 can include information for identifying syntacticviolations or issues. For example, Rules 368 can include one or morerules for performing syntactic checks. Syntactic checks can verify thatthe configuration of L_Model 270A is complete, and can help identifyconfigurations or rules that are not being used. Syntactic checks canalso verify that the configurations in the hierarchical MIM 200 arecomplete (have been defined) and identify any configurations that aredefined but not used. To illustrate, Rules 368 can specify that everytenant in L_Model 270A should have a context configured configured;every contract in L_Model 270A should specify a provider EPG and aconsumer EPG; every contract in L_Model 270A should specify a subject,filter, and/or port; etc.

Rules 368 can also include rules for performing semantic checks andidentifying semantic violations or issues. Semantic checks can checkconflicting rules or configurations. For example, Rule1 and Rule2 canhave aliasing issues, Rule1 can be more specific than Rule2 and therebycreate conflicts/issues, etc. Rules 368 can define conditions which mayresult in aliased rules, conflicting rules, etc. To illustrate, Rules368 can specify that an allow policy for a specific communicationbetween two objects can conflict with a deny policy for the samecommunication between two objects if the allow policy has a higherpriority than the deny policy, or a rule for an object renders anotherrule unnecessary.

Static Policy Analyzer 360 can apply Rules 368 to L_Model 270A to checkconfigurations in L_Model 270A and output Configuration Violation Events370 (e.g., alerts, logs, notifications, etc.) based on any issuesdetected. Configuration Violation Events 370 can include semantic orsemantic problems, such as incomplete configurations, conflictingconfigurations, aliased rules, unused configurations, errors, policyviolations, misconfigured objects, incomplete configurations, incorrectcontract scopes, improper object relationships, etc.

In some cases, Static Policy Analyzer 360 can iteratively traverse eachnode in a tree generated based on L_Model 270A and/or MIM 200, and applyRules 368 at each node in the tree to determine if any nodes yield aviolation (e.g., incomplete configuration, improper configuration,unused configuration, etc.). Static Policy Analyzer 360 can outputConfiguration Violation Events 370 when it detects any violations.

The disclosure now turns to FIGS. 4A and 4B, which illustrate examplemethods. FIG. 4A illustrates example method for network assurance, andFIG. 4B illustrates an example method for generating logical models. Themethods are provided by way of example, as there are a variety of waysto carry out the methods. Additionally, while the example methods areillustrated with a particular order of blocks or steps, those ofordinary skill in the art will appreciate that FIGS. 4A and 4B, and theblocks shown therein, can be executed in any order and can include feweror more blocks than illustrated.

Each block shown in FIGS. 4A and 4B represents one or more steps,processes, methods or routines in the methods. For the sake of clarityand explanation purposes, the blocks in FIGS. 4A and 4B are describedwith reference to Assurance Appliance 300, Models 270A-B, 272, 274, 276,and Network Environment 100, as shown in FIGS. 1A-B, 2D, and 3A.

FIG. 4A illustrates a flowchart for an example network assurance method.At step 400, Assurance Appliance 300 can collect data and obtain modelsassociated with Network Environment 100. The models can include Models270A-B, 272, 274, 276. The data can include fabric data (e.g., topology,switch, interface policies, application policies, EPGs, etc.), networkconfigurations (e.g., BDs, VRFs, L2 Outs, L3 Outs, protocolconfigurations, etc.), security configurations (e.g., contracts,filters, etc.), service chaining configurations, routing configurations,and so forth. Other information collected or obtained can include, forexample, network data (e.g., RIB/FIB, VLAN, MAC, ISIS, DB, BGP, OSPF,ARP, VPC, LLDP, MTU, QoS, etc.), rules and tables (e.g., TCAM rules,ECMP tables, etc.), endpoint dynamics (e.g., EPM, COOP EP DB, etc.),statistics (e.g., TCAM rule hits, interface counters, bandwidth, etc.).

At step 402, Assurance Appliance 300 can analyze and model the receiveddata and models. For example, Assurance Appliance 300 can perform formalmodeling and analysis, which can involve determining equivalency betweenmodels, including configurations, policies, etc.

At step 404, Assurance Appliance 300 can generate one or more smartevents. Assurance Appliance 300 can generate smart events using deepobject hierarchy for detailed analysis, such as Tenants, switches, VRFs,rules, filters, routes, prefixes, ports, contracts, subjects, etc.

At step 406, Assurance Appliance 300 can visualize the smart events,analysis and/or models. Assurance Appliance 300 can display problems andalerts for analysis and debugging, in a user-friendly GUI.

FIG. 4B illustrates an example method for generating a device specificlogical model, in accordance with various aspects of the subjecttechnology. At step 420, Assurance Appliance 300 can obtain, fromControllers 116, logical level configuration data associated withNetwork Environment 100. The logical level configuration data caninclude configurations or other models stored at Controllers 116 forNetwork Environment 100. The logical level configuration data may bebased, at least in part, on configuration information provided by anetwork administrator. Based on the logical level configuration data, atstep 422, Assurance Appliance 300 can generate a network-wide logicalmodel (e.g., L_Model 270A) of Network Environment 100. The network-widelogical model can represent a configuration of objects in a hierarchicalmanagement information tree (e.g., MIM 200) associated with the network.

At step 424, Assurance Appliance 300 can generate, based on thenetwork-wide logical model, a rendered logical model (e.g., LR_Model270B) of the network. The rendered logical model can include a runtimestate of the network. The rendered logical model can be formatted in amanner that can be read, executed, rendered, and/or interpreted bynetwork devices in Fabric 120, such as Leafs 104 and Spines 102. In somecases, the rendered logical model can be a flat model of thenetwork-wide logical model containing objects or identifiers that areunderstood by network devices in Fabric 120, such as JSON objects,hardware plane identifiers, policy group tags, etc.

Based on the rendered logical model, at step 426, Assurance Appliancecan generate, for one or more network devices in Network Environment 100(e.g., Leafs 104 in Fabric 120), a respective device-specificrepresentation of the network-wide logical model (e.g., Li_Model 272).The respective device-specific representation can project thenetwork-wide logical model onto a respective network device. In otherwords, the respective device-specific representation can convey how thenetwork-wide logical model should look or apply at the respectivenetwork device. For example, the respective device-specificrepresentation can be a switch-specific logical model that representsthe network-wide logical model as perceived, projected, applicable,etc., to the particular switch.

Network Node Memory Utilization Analysis

According to various aspects of the subject technology, one or morenetwork administrators can define a configuration or a set of intents atone or more network controllers (e.g., an APIC controller) or one ormore network assurance appliances of a network fabric. The networkscontroller may translate the set of intents into a machine-readable formand implement it across the network fabric (e.g., on spines, leafs, orother network nodes).

For example, the configuration or set of intents may initially be in anatural language format or a follow a human-readable syntax which can betranslated into a logical model format supported by the one or morenetwork controllers. In other implementations, the set of intents orconfiguration may be inputted in a logical model format. The one or morenetwork controllers may render the logical model level intents to aconcrete level for each network node, such that the concrete levelrendering of the logical level intents is readable by one or more nodes(e.g., leafs and/or spines) in the fabric to define configurations andother settings for endpoints, groups of endpoints, applications,services, etc. The concrete level intents may be rendered into hardwarelevel intents that are compatible with the operation of the nodes andthe physical memory or storage utilized by each node in the fabric. Thenetwork nodes, however, have limited memory.

For example, some network nodes may utilize Ternary Content-AddressableMemory (TCAM) to store the hardware level rendering of intents as aseries of TCAM entries. However, each node may have a limited amount ofTCAM memory and/or may only be able to store a limited number of TCAMentries. Furthermore, it is more difficult for network administrators tounderstand the specifics of what is happening at the TCAM level becauseTCAM entries are in a machine-readable format.

For example, it is difficult for a network administrator to understandthe function and/or purpose of specific TCAM entries. Furthermore, onceintents are rendered into the hardware level as TCAM entries, it isdifficult for network administrators to determine which logical levelintents, contracts, endpoint groups, or other logical level componentsthat TCAM entries are associated with. Knowing the logical levelcomponents that the TCAM entries are associated with may be helpful fornetwork administrators to determine which components (e.g., contracts,tenants, policies, etc.) use the most TCAM entries or memory. Theassociations of TCAM entries to logical level components may also behelpful to a network administrator when configuring or reconfiguring anetwork. For example, for various reasons, TCAM entries may becomeoutdated or there may be errors implementing the network intent in theTCAM entries of a network node (e.g., a leaf). Because of the difficultyfor network administrators to read or understand TCAM entries and whichlogical level components each TCAM entry is associated with, stale,missing TCAM entries, and/or erroneously implemented TCAM entries aredifficult to detect and remove.

A network assurance appliance may be configured to enrich TCAM entrieswith the logical level framework and associate the TCAM entries withvarious logical level components, concepts, dimensions, and/orhuman-readable annotations, in accordance with various aspects of thesubject technology. These logical level aspects are more human-readableand comprehensible to network administrators than TCAM entries. Forexample, the network assurance appliance may be able to associate TCAMentries with a particular source or destination tenant, contract, endpoint group, or other component or dimension of a logical level model.This information may be useful in debugging network issues, monitoringnetwork usage, contract management, tenant management, determining howmany TCAM entries are associated with various logical level components,or other network related activities.

In general, information contained in a logical model format may includehigh-level expressions of network configurations and/or logicalrepresentations of the network objects and their relationships. Thelogical model may represent an “end-state” expression of a desirednetwork intent (e.g., how the administrator wants the network andnetwork elements to behave) that should be implemented when the logicalmodel is correctly rendered into the concrete and hardware levels andimplemented on the appropriate network node.

The information at the concrete level (e.g., information stored in theconcrete model) may be derived from the logical level information andrepresents the actual in-state configuration at of a particular node inthe fabric (e.g., a leaf node, spine node, or other switch device). Theconcrete model for a node contains node-specific information based onthe logical model. For example, a network controller may provide thelogical model (e.g., the L model) or the logical model for the node(e.g., the Li model) to the appropriate node (e.g., the nodecorresponding to i). The node may render the logical model into aconcrete model that runs on the node. In other variations, the networkcontroller may render the logical model into the concrete model andprovide the concrete model to the node.

According to some implementations, the concrete level information may bein the form of access control (actrl) rules. Access control rulesprovide a granular method for a node to handle network traffic. In someaspects, each rule may include various filters or conditions that canspecify a type or category of network flows and an action that the nodewill perform on data packets matching those filters and conditions. Theactions may include, for example, monitoring, inspecting, trusting,redirecting, logging, blocking, allowing, or other actions that may beapplied to matching traffic.

The information at the hardware level (e.g., information stored in thehardware model) for a node is node-specific information rendered basedon the concrete level information for that node (e.g., the node'sconcrete model). The information at the hardware level may represent theactual configuration (e.g., entries) stored or rendered on the hardwareor memory (e.g., TCAM memory) at the individual node. According to someimplementations, the hardware level information may be in the form ofTCAM entries stored in the TCAM memory of a node. A node may store thevarious hardware level entries, use the entries to manage networktraffic flows, and provide an application program interface (e.g., anAPI) that allows a network controller or network assurance appliance toretrieve various data about the hardware level entries stored on thenode. For example, using the API, a network assurance appliance mayquery a node for a number of hardware level entries associated with aparticular concrete level network rule.

FIG. 5A illustrates an example method embodiment for determining anumber of hardware level entries for a logical level component, inaccordance with various aspects of the subject technology. Although themethods and processes described herein may be shown with certain stepsand operations in a particular order, additional, fewer, or alternativesteps and operations performed in similar or alternative orders, or inparallel, are within the scope of various embodiments unless otherwisestated. The method 500 may be implemented by a network assuranceappliance. However, in other variations, the method 500 may be performedby a network controller, another system, or a combination of systems.

At operation 502, a network assurance appliance may query a leaf node inthe network fabric for a number of hardware level entries associatedwith each concrete level network rule implemented on the leaf node. Theconcrete level network rules may be implemented on the leaf node toexpress the rendered concrete level intent for the leaf node and be oneof a number of concrete level network rules. The hardware level entriesmay be TCAM entries stored in the leaf node's TCAM memory and representa hardware level rendering of intents for the leaf node.

According to some aspects of the subject technology, the networkassurance appliance may determine the concrete level network rulesimplemented on a leaf node by querying an interface provided by the leafnode for that information (either as a list of concrete level networkrules or as an entire or portion of a concrete model for the node). Insome aspects, the concrete level network rules implemented on a leafnode may be obtained by querying a network controller for theinformation or by generating the information from one or more logicalmodels. The network assurance appliance may transmit a query, such asthe query in operation 502, to the leaf node for each concrete levelnetwork rule on the leaf node. In other aspects, the concrete levelnetwork rules implemented on a leaf node may be obtained as a result ofthe query to the leaf node at operation 502, where the leaf noderesponds to the query by providing one or more concrete level rulesimplemented on the leaf node and a number of hardware level entriesassociated with each of the one or more concrete level rules.

According to some aspects, the concrete level network rule may be in theform of an access control (actrl) rule in an ACI implemented networkfabric. Each actrl rule may be associated with a rule ID and the networkassurance appliance may query the leaf node to identify rule IDs foractrl rules implemented on the leaf node. For each actrl ruleimplemented on the leaf node (e.g., for each rule ID), the networkassurance appliance may query the leaf node to determine the number ofTCAM entries associated with that actrl rule or rule ID. The mapping ofactrl rule IDs to TCAM entries may be found in a zoning rule mappingstored by the leaf node. The network assurance appliance may retrievethe zoning rule mapping from the leaf node.

At operation 504, for each concrete level network rule, the networkassurance appliance may identify a logical level network intentassociated with the concrete level network rule at operation 506. Thelogical level network intent may be identified based on the logicalmodel for the node that contains relational information for logicallevel network intents in the logical model and concrete level networkrules that are rendered based on a corresponding logical level networkintent.

The logical level network intent may be embodied in one or morehigh-level policies, settings, configurations, etc. The logical levelnetwork intent may include higher-level concepts and be in a morehuman-readable format than concrete level rules or hardware levelentries. The logical level network intent may be tied specifically tothe leaf node rather than a fabric-wide logical intent and specify alogical intent for the leaf node. For example, logical level networkintent for the leaf node may be based on a logical model for the leafnode generated using the fabric-wide logical model. The logical levelnetwork intent for the leaf node may be associated with the concretelevel network rule and include a number of components that specify thelogical intent for that leaf node.

For example, the components of a logical level network intent mayinclude tenants, endpoint groups, endpoints, bridge domains, contracts,subjects, filters, ports or port ranges, protocols, or any otherannotations, actions, descriptors, or metrics associated with networkmanagement. These components may further be characterized as source ordestination (e.g., source tenant, source endpoint groups, destinationstenant, destination endpoint group, provider endpoint groups, consumerendpoint groups, etc.). Components may also include tags or labels thatcan annotate any of the above components or the logical level intentitself. These tags or labels may have various uses and be used to selectsets or subsets of intents or components.

According to some aspects of the subject technology, in addition toentities (e.g., endpoints, endpoint groups, etc.) having source anddestination relationships that reflect the source of data packets ordata flow from a source entity to a destination entity, the entities mayadditionally (or alternatively) have provider and consumerrelationships. The provider/consumer label reflects the relationshipbetween a provider of a policy contract and a consumer of a policycontract where the direction of data flow is less important. For exampleprovider entites expose contracts with which a would-be consumer entitycomplies. When an entity provides a policy or contract, communicationwith that entity proceeds according to the provided policy or contract.When an entity consumes a policy or contract, the consumer entitiescommunication with the provider entity according to the provided policyor contract.

At operation 508, the network assurance appliance may identify a set oflogical level components of the logical level network intent andattribute the number of hardware level entries to each of the logicallevel components at operation 510. As an illustrative example, inresponse to the querying in operation 502, the network assuranceappliance determines that N number of TCAM entries are associated with aparticular concrete level network rule and, in response to operation508, the network assurance appliance determines that that concrete levelnetwork rule is associated with components source EPG A, destination EPGB, contract C, and protocol TCP. At operation 510, the network assuranceappliance may attribute N TCAM entries to each of components source EPGA, destination EPG B, contract C, and protocol TCP. If there areadditional concrete level network rules to process, the method mayreturn to operation 504 to process the next concrete level network rule.

The number of TCAM entries associated to each component may beaggregated across concrete level network rules and stored by the networkassurance appliance in a database, table, or any other data structure inany memory format. FIG. 5B illustrates an example data structure tostore an association of a number of hardware level entries with logicallevel components, in accordance with various aspects of the subjecttechnology. As the concrete level network rules are processed in FIG.5A, the network assurance appliance may add the associated number ofhardware level entries (e.g., TCAM entries) to the appropriate logicallevel component. According to some aspects, the network assuranceappliance may also store a mapping of specific TCAM entries (e.g., basedon a TCAM entry identifier) to logical level components so that specificTCAM entries associated with a particular logical level component may bequeried or otherwise identified.

As a result of these steps, the network assurance appliance generates amapping of a total number of hardware level entries associated with eachlogical level component for the intents implemented by the leaf node.This information may be used by network administrators, applications, orservices for various uses. For example, the information may be used toidentify logical level components that are using the most hardware levelentries or leaf node memory, to provide various metrics to networkfabric tenants for informational uses, billing, etc., to identifyparticular logical level components that are misbehaving (e.g., using anabnormal number of hardware level entries), or to monitor leaf nodememory over time, which may be useful in debugging the network fabric(e.g., identifying a rule that is misbehaving on the hardware level) oranomaly detection.

According to some aspects of the subject technology, the networkassurance appliance perform similar operations on all or additionalnodes (e.g., leaf nodes) in the network fabric. For example, the networkassurance appliance may generate mappings of the total numbers ofhardware level entries in each node associated with the various logicallevel components implemented on the nodes. This information may beprovided to network administrators on a per-node basis, a per-networkfabric basis, or a combination.

The network assurance appliance may allow for the retrieval or queryingof the data and the presentation of the data in various forms (e.g.,pivot tables, spreadsheets, etc.). This information may be retrieved bya network administrator, application, service, or the network assuranceappliance itself through one or more interfaces. For example, returningto FIG. 5A, at operation 512, the network assurance appliance mayreceive, through an interface (e.g., an API), a request for a number ofhardware level entries associated with one or more (or all) logicallevel components of a node. At operation 514, the network assuranceappliance may retrieve and provide the number of hardware level entriesassociated with the selected logical level component(s).

Furthermore, the network assurance appliance may provide a detailedbreakdown of the leaf node memory utilization metrics via variousinterfaces. The network assurance appliance may be configured toprovide, for example, metrics on a total TCAM utilization per leaf node;TCAM utilization across the entire fabric per contract; TCAM utilizationby all contracts that have a particular filter attached; TCAMutilization across the entire fabric for a given EPG; TCAM utilizationacross the entire fabric by all EPGs that are associated with a givenBD; TCAM utilization across the entire fabric by all EPGs that areassociated with all BDs in a given VRF; or TCAM utilization across theentire fabric by all VRFs associated with a given tenant. To obtaininformation across the entire fabric or for other nodes in the fabric,the network assurance appliance may the method of FIG. 5A or similarmethods on additional nodes in the network fabric.

According to various aspects of the subject technology, the networkassurance appliance may rank logical level components based on thenumber of hardware level entries they use for a node, across a number ofselected nodes, or across the network fabric. The ranking may be for acategory of logical level components (e.g., ranking tenants, EPGs,contracts, based on the number logical level components associated witheach) or multiple categories of logical level components. The networkassurance appliance may also, or alternatively, identify one or morelogical level components that use the most hardware level entries in anode, across a number of selected nodes, or across the network fabric.

The network assurance appliance may perform the operations of method 500periodically (e.g., every 5 minutes) in order to determine the numbersof TCAM entries for various logical level components for that timeperiod. This information may be recorded and monitored over time inorder to identify and report anomalies, misconfigurations, problems,root causes for problems, or other issues.

For example, over time, the TCAM entries for a particular logical levelcomponent may be stable or fluctuate in a predictable manner or within arange. The network assurance appliance may detect or enable a networkadministrator to detect if the number of TCAM entries for the particularlogical level component deviate from an expected value or range. Thisdeviation may indicate a network problem. In another example, the numberof TCAM entries for a particular logical level component may beabnormally high compared to the numbers of TCAM entries for otherlogical level components. This deviation may also indicate a networkproblem.

FIGS. 6A-6E illustrate example user interfaces, in accordance withvarious aspects of the subject technology. The network assuranceappliance may provide various user interfaces or enable various userinterfaces for network administrators. For example, for each leaf node,the network assurance appliance may determine a percentage of TCAMmemory being used and provide the information to a networkadministrator. The information may also be aggregated over a number ofleaf nodes in the network fabric and provided to the user.

For example, FIG. 6A illustrates an example interface where a networkadministrator may select a network fabric for viewing using interfaceelement 602 and a particular time period at using interface element 604.In response to the selections, the network assurance appliance mayprovide information relating to TCAM utilization across a number of leafnodes in the selected network fabric at a particular time period. Thisinformation may be categorized into, for example, percentage utilizationas shown at 606.

FIG. 6B illustrates an example interface that provides a visualizationof the relationship between logical components, TCAM entries, and hitcounts. As will be discussed in further detail below, the networkassurance appliance may identify TCAM entries associated with logicallevel components, track hit counts for how often the TCAM entries areused or “hit,” and provide the information to a network administrator.Although the information may be sorted, organized, and presented invarious ways, FIG. 6B shows the least used TCAM entries by hit countorganized by the contract logical level component.

For example, each row may be for a particular contract, as indicated inthe contract column 608, and indicate a number of times in various timeperiods in columns 610 (e.g., in the past month, week, day, hour, orcumulative) that one or more TCAM entries associated with the contracthave been hit. At column 612, the interface shows how many TCAM entriesthere are that are associated with the contract for that row. Thisinformation may be presented to a network administrator so that they cantake informed action, provided to a network service, or acted upon bythe network assurance appliance. For example, based on this information,the network assurance appliance can recommend (or an administrator candetermine) contracts to remove (e.g., the contracts whose associatedTCAM entries never get hit and take up the most space in TCAM).

FIG. 6C illustrates an example interface that provides a visualizationof TCAM utilization of leaf nodes with respect to their correspondingcapacity. The leaf nodes may be ranked or organized based on the levelof utilization. In FIG. 6C, the leaf nodes are ranked based on thehighest percentage of utilization. Although the leaf nodes shown in FIG.6C all have the same capacity (e.g., each can store 61,000 TCAMentries), in other implementations, the leaf nodes may have differentcapacities.

FIG. 6D illustrates an example interface that provides variousnotifications for TCAM status on leaf nodes in a network fabric. Theinterface provides a way for the network assurance appliance to providea network administrator with information about the TCAM status on one ormore leaf nodes. In other aspects, however, the information may beprovided in other ways including a mobile application notification, anemail, a text message, etc. Various information and/or notifications maybe presented in the interface shown in FIG. 6D including that aparticular leaf node has stale entries 614 or that a leaf node is at aparticular level of TCAM utilization 616.

FIG. 6E illustrates an example interface that enables a user to selectparticular TCAM utilization information to view, query the networkassurance system for the selected TCAM utilization information, andvarious TCAM utilization information. For example, the interface in FIG.6E contains interface elements that enables a network administrator toselect TCAM utilization based on a leaf name 620, a provider tenant name622, a provider EPG name 624, a contract name 626, rule content 628, afilter name 630, or other information not shown. A query may be sent tothe network assurance appliance based on the selected options and thenetwork assurance appliance may provide a response that includes thenumber of hardware level entries (e.g., TCAM entries) associated withthe selected options. This information may be provided in the interfacein column 632.

Identifying Mismatches Between a Logical Model and Node Implementation

As described above, it is difficult for network administrators tounderstand the current configuration of the nodes at the hardware levelbecause the hardware level entries are often implemented in amachine-readable format that is more detached from logical componentassociations than at the logical level. These hardware level entries maybecome outdated, misconfigured, or out of sync with logical model levelintents over time for various reasons. For example, new logical levelpolicies may be added over time, certain logical level policies may beremoved, some logical level filters may overlap, network administratorsmay try to configure individual nodes, different network administratorsmay make changes to the fabric configuration that are unknown to othernetwork administrators, etc. This may cause hardware level entries(e.g., TCAM entries) stored in network node memory to become stale andnot relate to an active logical level intent, thereby needlessly takingup valuable memory space in the network node. These errors may bedifficult for a network administrator or network controller to detect.

A network assurance appliance may be configured to determine whether anode in the network fabric (e.g., a leaf node) has properly configuredthe concrete or hardware levels based on the logical level model, inaccordance with various aspects of the subject technology. The networkassurance appliance may identify a specific misconfigured node in thenetwork fabric and report that misconfigured node to a networkadministrator for action.

For example, in response to a notification that one or more nodes in thenetwork fabric is misconfigured, the network administrator may decide torestart or reboot the node, wipe node memory, recompile the hardwarelevel entries on the node, and/or reconfigure the node based on avalidated logical or concrete model. In some aspects, the networkassurance appliance may identify specific hardware level entries orconcrete rules that are stale or invalid and the network administratormay remove those entries or rules from the node. These actions may beperformed by the network administrator via an interface with the networkassurance appliance or the network controller. Furthermore, in somecases, the network assurance appliance may perform these tasksautomatically.

Two example categories of stale or misconfigured representations oflogical level intents in a node include when the hardware level entries(e.g., TCAM entries) do not accurately represent logical or concretelevel intents for the node or when concrete level rules (e.g., actrlrules) do not accurately represent logical level intents for the node.The network assurance appliance may determine that the concrete levelrules are not appropriately configured if, for example, one or moremappings of concrete level rules to logical level intents fails. Thenetwork assurance appliance may determine that the hardware levelentries are not appropriately configured if, for example, one or moremappings of hardware level entries to concrete level rules fails. Thenetwork assurance appliance may check for both categories ofmisconfigurations in parallel, sequentially, or in any other combinationof orders.

FIG. 7 illustrates an example method embodiment for determining whetherconcrete level rules implemented on a node are appropriately configured,in accordance with various aspects of the subject technology. Thenetwork assurance appliance may determine that the concrete level rulesare not appropriately configured on a node, such as a leaf node, bycomparing the concrete level rules implemented on a node with a set ofreference concrete level rules for the node that may be considered asource of truth or may represent a correct configuration of a particularnode.

At operation 702, the network assurance appliance may obtain one or morereference concrete level rules for a node in a network. The concretelevel rules may be in the form of, for example, access control (actrl)rules for an ACI or similar network. In some cases, the referenceconcrete level rules may be derived from one or more logical models.

For example, the network assurance appliance may obtain a logical modelfor the node (e.g., the Li model). In some situations, the networkassurance appliance may need to generate the logical model for the nodebased on the logical model for the network fabric (e.g., the L model).The logical model for the network fabric may be provided to the networkassurance appliance or obtained by querying a network controller. Usingthe Li model, the network assurance appliance may generate a concretemodel (e.g., the Ci model) that includes concrete level rules thatshould be implemented on the leaf node. These concrete level rulesgenerated from the logical model may be in the form of access control(actrl) rules and may be referred to as reference concrete level rules.

At operation 704, the network assurance appliance obtains implementedconcrete level rules from the node in the network. For example, eachnode in the network may store a concrete model which includes theconcrete level rules that are implemented on that node. The networkassurance appliance may poll one or more nodes in the network for theirconcrete models to obtain the implemented concrete level rules for oneor more nodes in the network. In other variations, however, the networkassurance appliance may obtain the implemented concrete level rules fromother sources.

The network assurance appliance may compare the reference concrete levelrules with the implemented concrete level rules at operation 706 anddetermine whether the implemented concrete level rules are appropriatelyconfigured based on the comparison at operation 708. For example, thenetwork assurance appliance may compare the number of reference concretelevel rules derived from the logical model for the node with the numberof implemented concrete level rules. If the numbers are not the same orthere is a mismatch, it is likely that there is a misconfiguration ofthe concrete level rules implemented on the node.

If there is a detected misconfiguration, the network assurance appliancemay notify a network administrator of the misconfiguration, make arecord of the misconfiguration and associated the occurrence of themisconfiguration with the time that the misconfiguration was detected,and/or attempt to reconfigure the node. For example, the networkassurance appliance may send instructions to the node or the networkcontroller to restart or reboot the node, wipe node memory, recompilethe hardware level entries on the node, and/or reconfigure the nodebased on a validated logical or concrete model.

If the numbers are the same, it is more likely that the concrete levelrules are appropriately configured and the network assurance appliancemay take no additional action. In some aspects, however, the networkassurance appliance may subsequently perform an additional check forwhether the hardware level entries are appropriately configured.

According to some aspects, instead of, or in addition to, comparing thenumber of reference concrete level rules derived from the logical modelfor the node with the number of implemented concrete level rules, thenetwork assurance appliance may compare the actual reference concretelevel rules derived from the logical model for the node with theimplemented concrete level rules to make sure that the two sets of rulesmatch. In other words, the network assurance appliance checks that eachof the reference concrete level rules are in the set of implementedconcrete level rules and each of the implemented concrete level rulesare in the set of reference concrete level rules. For example, thenetwork assurance appliance may compare the rule IDs for the referenceconcrete level rules with the rule IDs for the implemented concretelevel rules. If the all of the rule IDs match, the concrete level rulesare likely to be appropriately configured on the node.

If the rule IDs do not match, the concrete level rules may not beappropriately configured. Accordingly, the network assurance appliancemay take any of the above identified actions, remove implementedconcrete level rules that are not found in the reference concrete levelrules, and/or add implement concrete level rules from the referenceconcrete level rules that were not previously implemented. In somecases, the network assurance appliance can also reconfigure thecorresponding hardware level entries as appropriate.

According to some aspects, if the concrete level rules implemented on anode are determined to be inappropriately configured, the networkassurance appliance may reconfigure the node, which also reconfiguresthe hardware level entries (e.g., TCAM entries) on the node.Accordingly, in some implementations, the network assurance appliancemay not check the configuration of the hardware level entries on thenode. However, if the concrete level rules implemented on the node areproperly configured or in other implementations where perhaps the checksare performed in parallel, the network assurance appliance may alsodetermine whether the hardware level entries implemented on the node areproperly configured.

FIG. 8 illustrates an example method embodiment for determining whetherhardware level entries implemented on a node are appropriatelyconfigured, in accordance with various aspects of the subjecttechnology. The network assurance appliance may determine whether thehardware level entries are appropriately configured on a node, such as aleaf node, by comparing the hardware level entries implemented on thenode with a set of reference hardware level entries that may beconsidered a source of truth or may represent a correct configuration ofa particular node.

At operation 802, the network assurance appliance may obtain a set ofreference rule identifiers for concrete level rules for a node.According to some embodiments, the reference rule identifiers may begenerated by a network controller rendering a logical model into aconcrete model and/or hardware model. In some embodiments, the networkcontroller may also provide an API interface that enables a networkassurance appliance to query the network controller for concrete levelrules for the node and their associated rule identifiers. The networkcontroller may provide the concrete level rules for the node and theirassociated rule identifiers to the network assurance appliance inresponse to the query. In other implementations, however, the networkassurance appliance may obtain the set of reference rule identifiers forthe concrete level rules for the node by obtaining a logical model fromthe network controller, rendering the logical model into a concreteand/or hardware model, and extracting the information from the renderedmodels. The set of rule identifiers are associated with the concretelevel rules that reflect a proper configuration of the node based on thelogical model. Accordingly, this set of rule identifiers may beconsidered the reference rule identifiers.

At operation 804, implemented rule identifiers associated with hardwarelevel entries stored on the node may be obtained. The node may storehardware level entries (e.g., TCAM entries) in memory where each entrymay reference a rule identifier for a concrete level rule that the entryis based on. In other words, when a concrete level rule is rendered asone or more hardware level entries, each of the hardware level entrieswill include a rule identifier for that concrete level rule.Accordingly, the network assurance appliance may query the node toobtain the rule identifiers associated with the hardware level entries.

At operation 806, the reference rule identifiers and the implementedrule identifiers may be compared and the network assurance appliance maydetermine whether the hardware level entries implemented on the node areappropriately configured based on the comparison at operation 808. Ifthe reference rule identifiers and the implemented rule identifiers aredifferent, there is a mismatch and the hardware level entriesimplemented on the node are not properly configured. According to someaspects, the network assurance appliance may determine the number ofreference rule identifiers and the number of implemented ruleidentifiers and compare the two numbers. If the number of implementedrule identifiers different from the number of reference ruleidentifiers, there is a mismatch and the hardware level entriesimplemented on the node are not properly configured.

If the hardware level entries are not properly configured, the networkassurance appliance may notify a network administrator or service, log arecord of the misconfiguration, and/or try to resolve themisconfiguration by doing one or more of restarting or rebooting thenode, wiping node memory, recompiling the hardware level entries on thenode, and/or reconfiguring the node based on a validated logical orconcrete model.

According to some aspects of the subject technology, the networkassurance appliance may also identify implemented rule identifiers thatare not in the set of reference rule identifiers. These may be a resultof stale hardware level entries associated with rule identifiers forconcrete level rules that no longer exist. These stale hardware levelentries may be reported to a network administrator or the networkassurance appliance may attempt to remove the stale hardware levelentries.

Additionally, the network assurance appliance may attempt to calculate anumber of stale hardware level entries (e.g., TCAM entries) associatedwith the stale rule identifiers by querying the node for a number ofhardware level entries associated with each implemented rule identifierthat was not found in the set of reference rule identifiers and summingup the numbers provided in the response(s). Alternatively, the networkassurance appliance may obtain a number of implemented hardware levelentries and a number of reference hardware level entries, take thedifference between the two numbers, and use the difference as the numberof stale hardware level entries. The number of stale hardware levelentries may also be reported to a network administrator or the networkassurance appliance may attempt to remove the stale hardware levelentries.

FIG. 6D illustrates an interface that may be used to notify a networkadministrator that a particular node has stale TCAM entries. Forexample, the interface includes a notification 614 that a node has staleTCAM entries. If the network administrator selects the notification 614,additional information may be provided including, for example, thenumber of stale TCAM entries, the number and/or rule ID for staleconcrete level rules, or other related information.

According to some aspects, although various processes described hereinrelate to the network assurance appliance operating on one node, it isunderstood that the network assurance appliance may operate on all or aset of nodes in the network to gain a fuller picture of the currentstatus of the network.

Identifying Candidate Rules for Removal in a Node

As mentioned above, memory on a node for storing hardware level entriesis a limited and expensive resource. Even if the hardware level entriesare properly configured, without stale entries, the hardware levelentries (e.g., TCAM entries) needed to implement the logical intent andall of the contracts represented in the logical intent may exceed thememory space of some nodes. Furthermore, network administrators have atendency to continue adding more and more contracts over time withoutremoving existing contracts and these contracts need more and morehardware level entries on nodes.

However, in the typical course of operation, some of these contractsand/or hardware level entries never get “hit.” In other words, theconditions applied by the contracts and/or hardware level entries arenever fulfilled such that the contracts or hardware level entriesdictate the flow of data through the network. Not only does this meanthat there are hardware level entries stored in node memory that are notused in the typical course of operation, but there may be securityvulnerabilities in the network (via the hardware level entries thatnever get hit) by allowing for some traffic that doesn't normally flowfor legitimate reasons. These vulnerabilities may allow malicious actorsto do harm to the network.

Various aspects of the subject technology determine whether concretelevel rules and/or hardware level entries are being hit and associatethose hardware level entries with various logical level components. Thisinformation may be presented to a network administrator so that they cantake informed action, provided to a network service, or acted upon bythe network assurance appliance. For example, based on this information,the network assurance appliance can recommend (or an administrator candetermine) which concrete level rules that may be removed (e.g., theconcrete level rules that never get hit and take up the most space inTCAM). For example, the network administrator may be provided with aninterface that allows the network administrator to quickly determinewhich unused concrete level rule is taking up the most space in TCAMmemory for a node (e.g., a leaf node).

The network assurance appliance may associate hit counts for concretelevel rules with logical level components such as contracts, source ordestination endpoints, source or destination EPGs, etc. The networkassurance appliance may also determine the number of hardware levelentries associated with the logical level components and provide theinformation in a report to a network administrator. The networkadministrator may use the information about how many hits a componenthas received and the number of hardware level entries associated withthe component to make changes to the network.

For example, the network administrator may remove one or more contracts,which are logical level components, that receive no hits but have manyassociated hardware level entries. The removal may increase availablememory space on the node. In some cases, the network administrator mayview a number of contracts that have no hits and the number of hardwareentries associated with each contract to make a more informed decision.For example, the network assurance appliance may recommend or thenetwork administrator may select the contract with no hits that has themost hardware level entries associated with it in order to clear up themost memory space on the node.

For example, FIG. 6B illustrates an example interface that provides avisualization of the relationship between logical level components, TCAMentries, and hit counts. The interface may enable a networkadministrator to view the hit counts for certain logical levelcomponents as well as the number of TCAM entries associated with thelogical level components. Although the information may be sorted,organized, and presented in various ways, FIG. 6B shows the least usedTCAM entries by hit count organized by the contract logical levelcomponent. In other words, the interface shows the logical levelcomponents with the most TCAM entries and the lowest hit counts. Suchinformation may be helpful to a network administrator because thenetwork administrator may not wish to remove logical level components(e.g., contracts) that are used. Furthermore, if the networkadministrator were to remove a logical level component (e.g., acontract), they may wish to remove an unused logical level componentassociated with the most TCAM entries in order to free up more space.

For example, each row may be for a particular contract, as indicated inthe contract column 608, and indicate a number of times in various timeperiods in columns 610 (e.g., in the past month, week, day, hour, orcumulative) that one or more TCAM entries associated with the contracthave been hit. At column 612, the interface shows how many TCAM entriesthere are that are associated with the contract for that row. Thisinformation may be presented to a network administrator so that they cantake informed action, provided to a network service, or acted upon bythe network assurance appliance. For example, based on this information,the network assurance appliance can recommend (or an administrator candetermine) contracts to remove (e.g., the contracts whose associatedTCAM entries never get hit and take up the most space in TCAM).According to some aspects, a network administrator may also use theinterface to select certain logical level components such as contractsand remove them from the network configurations.

FIG. 9 illustrates an example method embodiment for generating a reporton hit count for various logical level components, in accordance withvarious aspects of the subject technology. At operation 902, the networkassurance appliance may determine a hit count for each concrete levelrule (e.g., an access control rule) in a node. The network fabric may beconfigured to track hits for various concrete level rules. The networkassurance appliance may obtain the hit count for a particular concretelevel rule by querying the node or the network controller. The query maybe for a specifically referenced concrete level rule or for all concretelevel rules implemented on the node. In one implementation, the networkassurance appliance may query the node to identify rule IDs for concretelevel rules (e.g., actrl rules) implemented on the node and use the ruleIDs to request the hit counts for those concrete level rules in one ormore queries.

The hit count may be determined for a period of time (e.g., a week, amonth, or other length of time). Concrete level rules are typicallyallow rules allowing data flow under certain conditions or deny rulesdenying data flow under certain conditions. A hit on a rule may occurwhen a data packet meeting the conditions for the rule is allowed for anallow rule or denied for a deny rule.

Turning to operation 904, for each concrete level rule on the node, thenetwork assurance appliance may identify one or more components of alogical model that are associated with the concrete level rule atoperation 906. For example, as described above, the network assuranceappliance may identify a logical level network intent associated withthe concrete level network rule. The logical level network intent forthe node may include a number of components that specify the logicalintent for that node. These components may include tenants, endpointgroups, endpoints, bridge domains, contracts, subjects, or otherannotations, descriptors, or metrics associated with network management.

At operation 908, the network assurance appliance may attribute the hitcount for the concrete level rule to each of the one or more componentsof the logical model. This process may be repeated for each concretelevel rule on the node in order to build a hit count repository forcomponents of the logical mode. This information may be stored by thenetwork assurance appliance.

At operation 910, the network assurance appliance may determine a numberof hardware level entries associated with each of the one or morecomponents of the logical model. For example, the network assuranceappliance may query the node in the network fabric for a number ofhardware level entries associated with each concrete level rule.

At operation 912, the network assurance appliance may generate a reportthat illustrates the relationship between components of the logicalmodel, hit counts, and hardware level entries. For example, the reportmay include one or more components with the lowest hit counts and thenumber of hardware level entries associated with the component with thelowest hit count. In many cases, the lowest hit count will be 0 forcomponents that did not receive any hits. The network administrator mayuse this information to debug the network, reconfigure the network, orrequest changes from network tenants. For example, if a specificcontract receives no hits, the network administrator may remove thecontract or request the network tenant responsible for the contract toremove it. According to some aspects, the report may be provided in aninterface such as the interface illustrated in FIG. 6B that provides avisualization of the relationship between logical level components, TCAMentries, and hit counts.

The report may rank components, such as contracts, based on the numberof hardware level entries that the component is responsible for in thenode memory. Accordingly, the network administrator may identifycontracts or other components with the most hardware level entries andremove those contracts first. According to other aspects of the subjecttechnology, the report may also include hit count trends over time. Thismay be helpful for network administrators in debugging the network,attack detection, anomaly detection, and/or resource provisioning.

The disclosure now turns to FIGS. 10 and 11, which illustrate examplenetwork devices and computing devices, such as switches, routers, loadbalancers, client devices, and so forth.

FIG. 10 illustrates an example network device 1000 suitable forperforming switching, routing, load balancing, and other networkingoperations. Network device 1000 includes a central processing unit (CPU)1004, interfaces 1002, and a bus 1010 (e.g., a PCI bus). When actingunder the control of appropriate software or firmware, the CPU 1004 isresponsible for executing packet management, error detection, and/orrouting functions. The CPU 1004 preferably accomplishes all thesefunctions under the control of software including an operating systemand any appropriate applications software. CPU 1004 may include one ormore processors 1008, such as a processor from the INTEL X86 family ofmicroprocessors. In some cases, processor 1008 can be specially designedhardware for controlling the operations of network device 1000. In somecases, a memory 1006 (e.g., non-volatile RAM, ROM, etc.) also forms partof CPU 1004. However, there are many different ways in which memorycould be coupled to the system.

The interfaces 1002 are typically provided as modular interface cards(sometimes referred to as “line cards”). Generally, they control thesending and receiving of data packets over the network and sometimessupport other peripherals used with the network device 1000. Among theinterfaces that may be provided are Ethernet interfaces, frame relayinterfaces, cable interfaces, DSL interfaces, token ring interfaces, andthe like. In addition, various very high-speed interfaces may beprovided such as fast token ring interfaces, wireless interfaces,Ethernet interfaces, Gigabit Ethernet interfaces, ATM interfaces, HSSIinterfaces, POS interfaces, FDDI interfaces, WIFI interfaces, 3G/4G/5Gcellular interfaces, CAN BUS, LoRA, and the like. Generally, theseinterfaces may include ports appropriate for communication with theappropriate media. In some cases, they may also include an independentprocessor and, in some instances, volatile RAM. The independentprocessors may control such communications intensive tasks as packetswitching, media control, signal processing, crypto processing, andmanagement. By providing separate processors for the communicationsintensive tasks, these interfaces allow the master microprocessor 604 toefficiently perform routing computations, network diagnostics, securityfunctions, etc.

Although the system shown in FIG. 10 is one specific network device ofthe present invention, it is by no means the only network devicearchitecture on which the present invention can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc., is often used.Further, other types of interfaces and media could also be used with thenetwork device 1000.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 1006) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc. Memory 1006could also hold various software containers and virtualized executionenvironments and data.

The network device 1000 can also include an application-specificintegrated circuit (ASIC), which can be configured to perform routingand/or switching operations. The ASIC can communicate with othercomponents in the network device 1000 via the bus 1010, to exchange dataand signals and coordinate various types of operations by the networkdevice 1000, such as routing, switching, and/or data storage operations,for example.

FIG. 11 illustrates a computing system architecture 1100 wherein thecomponents of the system are in electrical communication with each otherusing a connection 1105, such as a bus. Exemplary system 1100 includes aprocessing unit (CPU or processor) 1110 and a system connection 1105that couples various system components including the system memory 1115,such as read only memory (ROM) 1120 and random access memory (RAM) 1125,to the processor 1110. The system 1100 can include a cache of high-speedmemory connected directly with, in close proximity to, or integrated aspart of the processor 1110. The system 1100 can copy data from thememory 1115 and/or the storage device 1130 to the cache 1112 for quickaccess by the processor 1110. In this way, the cache can provide aperformance boost that avoids processor 1110 delays while waiting fordata. These and other modules can control or be configured to controlthe processor 1110 to perform various actions. Other system memory 1115may be available for use as well. The memory 1115 can include multipledifferent types of memory with different performance characteristics.The processor 1110 can include any general purpose processor and ahardware or software service, such as service 1 1132, service 2 1134,and service 3 1136 stored in storage device 1130, configured to controlthe processor 1110 as well as a special-purpose processor where softwareinstructions are incorporated into the actual processor design. Theprocessor 1110 may be a completely self-contained computing system,containing multiple cores or processors, a bus, memory controller,cache, etc. A multi-core processor may be symmetric or asymmetric.

To enable user interaction with the computing device 1100, an inputdevice 1145 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 1135 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 1100. The communications interface1140 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 1130 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 1125, read only memory (ROM) 1120, andhybrids thereof.

The storage device 1130 can include services 1132, 1134, 1136 forcontrolling the processor 1110. Other hardware or software modules arecontemplated. The storage device 1130 can be connected to the systemconnection 1105. In one aspect, a hardware module that performs aparticular function can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 1110, connection 1105, output device1135, and so forth, to carry out the function.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

Claim language reciting “at least one of” refers to at least one of aset and indicates that one member of the set or multiple members of theset satisfy the claim. For example, claim language reciting “at leastone of A and B” means A, B, or A and B.

What is claimed is:
 1. A computer-implemented method comprising:querying a leaf node in a network fabric for hardware level entriesassociated with concrete level network rules implemented on the leafnode, the hardware level entries stored in a memory for the leaf node;for each of the concrete level network rules, identifying one of aplurality of logical level network intents implemented on the leaf node,each of the plurality of logical level network intents associated withone of the concrete level network rules, each of the plurality oflogical level network intents identified based on a logical model withrelational information for the plurality of logical level networkintents and the concrete level network rules; identifying logical levelcomponents of the one of the plurality of logical level network intents;and attributing the hardware level entries to each of the logical levelcomponents.
 2. The computer-implemented method of claim 1, furthercomprising: receiving a query for a total number of the hardware levelentries associated with a selected one of the logical level components;and providing the total number in response to the query.
 3. Thecomputer-implemented method of claim 1, further comprising: generating amapping of a total number of the hardware level entries to the logicallevel components for logical level network intents implemented on theleaf node based on the number of hardware level entries attributed toeach of the logical level components; and providing the total number ofthe hardware level entries to an interface.
 4. The computer-implementedmethod of claim 1, further comprising: receiving, from the leaf node,the concrete level network rules implemented on the leaf node.
 5. Thecomputer-implemented method of claim 4, further comprising: querying theleaf node for the concrete level network rules implemented on the leafnode.
 6. The computer-implemented method of claim 4, wherein theconcrete level network rules implemented on the leaf node received fromthe leaf node comprises zoning rule mapping information.
 7. Thecomputer-implemented method of claim 1, wherein the memory for the leafnode is a Ternary Content-Addressable Memory (TCAM) and the hardwarelevel entries comprises at least one TCAM entry.
 8. Thecomputer-implemented method of claim 1, wherein the logical levelcomponents comprise at least one of a contract, an endpoint, an endpointgroup, a bridge domain, or a protocol.
 9. The computer-implementedmethod of claim 1, wherein the concrete level network rule is an accesscontrol (actrl) rule.
 10. A system comprising: one or more processors;and at least one computer-readable storage medium storing instructionswhich, when executed by the one or more processors, cause the system to:query a node in a network fabric for hardware level entries associatedwith a concrete level network rule, the hardware level entries stored ina memory for the node; identify one of a plurality of logical levelnetwork intents associated with the concrete level network rule, each ofthe plurality of logical level network intents identified based on alogical model with relational information for the plurality of logicallevel network intents and the concrete level network rule; identify alogical level component of the plurality of logical level networkintents; attribute the hardware level entries to the logical levelcomponent; and provide the hardware level entries to an interface. 11.The system of claim 10, wherein the node is a leaf node in the networkfabric.
 12. The system of claim 10, wherein the instructions furthercause the system to process a query for the hardware level entriesassociated with the logical level component by providing the hardwarelevel entries to the interface in response to the query.
 13. The systemof claim 10, wherein the instructions further cause the system to:generate a mapping of a total number of hardware level entries tological level component for logical level network intents implemented onthe node based on the number of hardware level entries attributed to thelogical level component; and provide the total number of hardware levelentries to the interface.
 14. The system of claim 10, wherein theinterface is a web interface configured to provide status informationfor the network fabric to a network administrator.
 15. A non-transitorycomputer-readable medium comprising instructions, the instructions, whenexecuted by a computing system, cause the computing system to: determineconcrete level network rules implemented on a leaf node; for each of theconcrete level network rules, query the leaf node in a network fabricfor hardware level entries associated with the concrete level networkrules; identify one of a plurality of logical level network intentsimplemented on the leaf node, each of the plurality of logical levelnetwork intents associated with one of the concrete level network rules,each of the plurality of logical level network intents identified basedon a logical model with relational information for the plurality oflogical level network intents and the concrete level network rules;identify logical level components of the one of the plurality of logicallevel network intents; and attribute the hardware level entries to eachof the logical level components; and generate a mapping of a totalnumber of the hardware level entries to the logical level components forlogical level network intents implemented on the leaf node based on thenumber of hardware level entries attributed to each logical levelcomponent in the logical level components.
 16. The non-transitorycomputer-readable medium of claim 15, wherein the instructions furthercause the computing system to provide the total number of the hardwarelevel entries to a network administrator.
 17. The non-transitorycomputer-readable medium of claim 16, wherein the instructions furthercause the computing system to process a query for the total number ofthe hardware level entries by providing the total number of the hardwarelevel entries in response to the query.
 18. The non-transitorycomputer-readable medium of claim 15, wherein the instructions furthercause the computing system to receive, from the leaf node, the concretelevel network rules implemented on the leaf node.
 19. The non-transitorycomputer-readable medium of claim 15, wherein the number of hardwarelevel entries comprises at least one Ternary Content-Addressable Memory(TCAM) entry.
 20. The non-transitory computer-readable medium of claim15, wherein the logical level components comprise at least one of acontract, an endpoint, an endpoint group, a bridge domain, or aprotocol.